diff --git a/docs/_posts/ahmedlone127/2024-09-01-finetuned_bge_embeddings_v3_base_v1_5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-01-finetuned_bge_embeddings_v3_base_v1_5_pipeline_en.md
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@@ -0,0 +1,69 @@
+---
+layout: model
+title: English finetuned_bge_embeddings_v3_base_v1_5_pipeline pipeline BGEEmbeddings from austinpatrickm
+author: John Snow Labs
+name: finetuned_bge_embeddings_v3_base_v1_5_pipeline
+date: 2024-09-01
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_bge_embeddings_v3_base_v1_5_pipeline` is a English model originally trained by austinpatrickm.
+
+{:.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/finetuned_bge_embeddings_v3_base_v1_5_pipeline_en_5.5.0_3.0_1725229508197.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_bge_embeddings_v3_base_v1_5_pipeline_en_5.5.0_3.0_1725229508197.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
+
+pipeline = PretrainedPipeline("finetuned_bge_embeddings_v3_base_v1_5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_bge_embeddings_v3_base_v1_5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_bge_embeddings_v3_base_v1_5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|387.1 MB|
+
+## References
+
+https://huggingface.co/austinpatrickm/finetuned_bge_embeddings_v3_base_v1.5
+
+## Included Models
+
+- DocumentAssembler
+- BGEEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-01-roberta_classifier_emotion_english_distil_base_en.md b/docs/_posts/ahmedlone127/2024-09-01-roberta_classifier_emotion_english_distil_base_en.md
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--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-01-roberta_classifier_emotion_english_distil_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_classifier_emotion_english_distil_base RoBertaForSequenceClassification from j-hartmann
+author: John Snow Labs
+name: roberta_classifier_emotion_english_distil_base
+date: 2024-09-01
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.4.2
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_classifier_emotion_english_distil_base` is a English model originally trained by j-hartmann.
+
+{:.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/roberta_classifier_emotion_english_distil_base_en_5.4.2_3.0_1725167903299.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_classifier_emotion_english_distil_base_en_5.4.2_3.0_1725167903299.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta_classifier_emotion_english_distil_base","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_classifier_emotion_english_distil_base", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_classifier_emotion_english_distil_base|
+|Compatibility:|Spark NLP 5.4.2+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|308.8 MB|
+
+## References
+
+https://huggingface.co/j-hartmann/emotion-english-distilroberta-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-02-sent_muril_base_cased_en.md b/docs/_posts/ahmedlone127/2024-09-02-sent_muril_base_cased_en.md
new file mode 100644
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--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-02-sent_muril_base_cased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_muril_base_cased BertSentenceEmbeddings from google
+author: John Snow Labs
+name: sent_muril_base_cased
+date: 2024-09-02
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_muril_base_cased` is a English model originally trained by google.
+
+{:.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/sent_muril_base_cased_en_5.5.0_3.0_1725274394892.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_muril_base_cased_en_5.5.0_3.0_1725274394892.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_muril_base_cased","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_muril_base_cased","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_muril_base_cased|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|890.4 MB|
+
+## References
+
+https://huggingface.co/google/muril-base-cased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-bislama_all_bs320_vanilla_finetuned_webnlg2020_relevance_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-bislama_all_bs320_vanilla_finetuned_webnlg2020_relevance_pipeline_en.md
new file mode 100644
index 00000000000000..ac04812040a7df
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-bislama_all_bs320_vanilla_finetuned_webnlg2020_relevance_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bislama_all_bs320_vanilla_finetuned_webnlg2020_relevance_pipeline pipeline MPNetEmbeddings from teven
+author: John Snow Labs
+name: bislama_all_bs320_vanilla_finetuned_webnlg2020_relevance_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bislama_all_bs320_vanilla_finetuned_webnlg2020_relevance_pipeline` is a English model originally trained by teven.
+
+{:.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/bislama_all_bs320_vanilla_finetuned_webnlg2020_relevance_pipeline_en_5.5.0_3.0_1725350188221.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bislama_all_bs320_vanilla_finetuned_webnlg2020_relevance_pipeline_en_5.5.0_3.0_1725350188221.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
+
+pipeline = PretrainedPipeline("bislama_all_bs320_vanilla_finetuned_webnlg2020_relevance_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bislama_all_bs320_vanilla_finetuned_webnlg2020_relevance_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bislama_all_bs320_vanilla_finetuned_webnlg2020_relevance_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.3 MB|
+
+## References
+
+https://huggingface.co/teven/bi_all_bs320_vanilla_finetuned_WebNLG2020_relevance
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-custom_mpnet_base_v2_en.md b/docs/_posts/ahmedlone127/2024-09-03-custom_mpnet_base_v2_en.md
new file mode 100644
index 00000000000000..4063afa43a7cbe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-custom_mpnet_base_v2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English custom_mpnet_base_v2 MPNetEmbeddings from 17nshul
+author: John Snow Labs
+name: custom_mpnet_base_v2
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`custom_mpnet_base_v2` is a English model originally trained by 17nshul.
+
+{:.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/custom_mpnet_base_v2_en_5.5.0_3.0_1725350331697.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/custom_mpnet_base_v2_en_5.5.0_3.0_1725350331697.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("custom_mpnet_base_v2","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("custom_mpnet_base_v2","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|custom_mpnet_base_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/17nshul/custom-mpnet-base-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_conll2003_breast_castellon_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_conll2003_breast_castellon_v1_pipeline_en.md
new file mode 100644
index 00000000000000..7710cf7b0f5359
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-deberta_v3_large_conll2003_breast_castellon_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_large_conll2003_breast_castellon_v1_pipeline pipeline DeBertaForTokenClassification from Yanis
+author: John Snow Labs
+name: deberta_v3_large_conll2003_breast_castellon_v1_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_conll2003_breast_castellon_v1_pipeline` is a English model originally trained by Yanis.
+
+{:.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/deberta_v3_large_conll2003_breast_castellon_v1_pipeline_en_5.5.0_3.0_1725388542562.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_conll2003_breast_castellon_v1_pipeline_en_5.5.0_3.0_1725388542562.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
+
+pipeline = PretrainedPipeline("deberta_v3_large_conll2003_breast_castellon_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large_conll2003_breast_castellon_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_conll2003_breast_castellon_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/Yanis/deberta-v3-large_conll2003_breast-castellon-v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_sharanharsoor_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_sharanharsoor_en.md
new file mode 100644
index 00000000000000..a620bfdd9f717f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_base_uncased_finetuned_imdb_sharanharsoor_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_sharanharsoor DistilBertEmbeddings from sharanharsoor
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_sharanharsoor
+date: 2024-09-03
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_sharanharsoor` is a English model originally trained by sharanharsoor.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_sharanharsoor_en_5.5.0_3.0_1725385235023.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_sharanharsoor_en_5.5.0_3.0_1725385235023.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_sharanharsoor","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_sharanharsoor","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_sharanharsoor|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/sharanharsoor/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-distilbert_persian_farsi_zwnj_base_finetuned_lm_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-distilbert_persian_farsi_zwnj_base_finetuned_lm_pipeline_en.md
new file mode 100644
index 00000000000000..b649e6486a677a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-distilbert_persian_farsi_zwnj_base_finetuned_lm_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_persian_farsi_zwnj_base_finetuned_lm_pipeline pipeline DistilBertEmbeddings from 4h0r4
+author: John Snow Labs
+name: distilbert_persian_farsi_zwnj_base_finetuned_lm_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_persian_farsi_zwnj_base_finetuned_lm_pipeline` is a English model originally trained by 4h0r4.
+
+{:.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/distilbert_persian_farsi_zwnj_base_finetuned_lm_pipeline_en_5.5.0_3.0_1725389504137.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_persian_farsi_zwnj_base_finetuned_lm_pipeline_en_5.5.0_3.0_1725389504137.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
+
+pipeline = PretrainedPipeline("distilbert_persian_farsi_zwnj_base_finetuned_lm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_persian_farsi_zwnj_base_finetuned_lm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_persian_farsi_zwnj_base_finetuned_lm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|282.3 MB|
+
+## References
+
+https://huggingface.co/4h0r4/distilbert-fa-zwnj-base-finetuned-lm
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-nerel_bio_rubioroberta_base_en.md b/docs/_posts/ahmedlone127/2024-09-03-nerel_bio_rubioroberta_base_en.md
new file mode 100644
index 00000000000000..50edc37b1bc0ec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-nerel_bio_rubioroberta_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English nerel_bio_rubioroberta_base RoBertaForTokenClassification from ekaterinatao
+author: John Snow Labs
+name: nerel_bio_rubioroberta_base
+date: 2024-09-03
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nerel_bio_rubioroberta_base` is a English model originally trained by ekaterinatao.
+
+{:.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/nerel_bio_rubioroberta_base_en_5.5.0_3.0_1725383973406.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nerel_bio_rubioroberta_base_en_5.5.0_3.0_1725383973406.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("nerel_bio_rubioroberta_base","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("nerel_bio_rubioroberta_base", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nerel_bio_rubioroberta_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/ekaterinatao/nerel-bio-RuBioRoBERTa-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-opensearch_neural_sparse_encoding_v2_distill_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-opensearch_neural_sparse_encoding_v2_distill_pipeline_en.md
new file mode 100644
index 00000000000000..78276c68677a93
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-opensearch_neural_sparse_encoding_v2_distill_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opensearch_neural_sparse_encoding_v2_distill_pipeline pipeline DistilBertEmbeddings from opensearch-project
+author: John Snow Labs
+name: opensearch_neural_sparse_encoding_v2_distill_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opensearch_neural_sparse_encoding_v2_distill_pipeline` is a English model originally trained by opensearch-project.
+
+{:.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/opensearch_neural_sparse_encoding_v2_distill_pipeline_en_5.5.0_3.0_1725384776382.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opensearch_neural_sparse_encoding_v2_distill_pipeline_en_5.5.0_3.0_1725384776382.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
+
+pipeline = PretrainedPipeline("opensearch_neural_sparse_encoding_v2_distill_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opensearch_neural_sparse_encoding_v2_distill_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opensearch_neural_sparse_encoding_v2_distill_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/opensearch-project/opensearch-neural-sparse-encoding-v2-distill
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-qa_synth_29_sept_with_finetune_1_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-qa_synth_29_sept_with_finetune_1_1_pipeline_en.md
new file mode 100644
index 00000000000000..ccf158dab1d83d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-qa_synth_29_sept_with_finetune_1_1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qa_synth_29_sept_with_finetune_1_1_pipeline pipeline XlmRoBertaForQuestionAnswering from am-infoweb
+author: John Snow Labs
+name: qa_synth_29_sept_with_finetune_1_1_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_synth_29_sept_with_finetune_1_1_pipeline` is a English model originally trained by am-infoweb.
+
+{:.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/qa_synth_29_sept_with_finetune_1_1_pipeline_en_5.5.0_3.0_1725380786297.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_synth_29_sept_with_finetune_1_1_pipeline_en_5.5.0_3.0_1725380786297.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
+
+pipeline = PretrainedPipeline("qa_synth_29_sept_with_finetune_1_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qa_synth_29_sept_with_finetune_1_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_synth_29_sept_with_finetune_1_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|804.6 MB|
+
+## References
+
+https://huggingface.co/am-infoweb/QA_SYNTH_29_SEPT_WITH_FINETUNE_1.1
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_base_sst_2_16_13_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_sst_2_16_13_pipeline_en.md
new file mode 100644
index 00000000000000..cdb055ef95c47c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_base_sst_2_16_13_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_sst_2_16_13_pipeline pipeline RoBertaForSequenceClassification from simonycl
+author: John Snow Labs
+name: roberta_base_sst_2_16_13_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_sst_2_16_13_pipeline` is a English model originally trained by simonycl.
+
+{:.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/roberta_base_sst_2_16_13_pipeline_en_5.5.0_3.0_1725403332163.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_sst_2_16_13_pipeline_en_5.5.0_3.0_1725403332163.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
+
+pipeline = PretrainedPipeline("roberta_base_sst_2_16_13_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_sst_2_16_13_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_sst_2_16_13_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|416.1 MB|
+
+## References
+
+https://huggingface.co/simonycl/roberta-base-sst-2-16-13
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_finetuned_state2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_finetuned_state2_pipeline_en.md
new file mode 100644
index 00000000000000..785c670d2a68ea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-roberta_qa_finetuned_state2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_finetuned_state2_pipeline pipeline RoBertaForQuestionAnswering from skandaonsolve
+author: John Snow Labs
+name: roberta_qa_finetuned_state2_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_finetuned_state2_pipeline` is a English model originally trained by skandaonsolve.
+
+{:.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/roberta_qa_finetuned_state2_pipeline_en_5.5.0_3.0_1725370920161.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_finetuned_state2_pipeline_en_5.5.0_3.0_1725370920161.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
+
+pipeline = PretrainedPipeline("roberta_qa_finetuned_state2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_finetuned_state2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_finetuned_state2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.8 MB|
+
+## References
+
+https://huggingface.co/skandaonsolve/roberta-finetuned-state2
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_bert_tiny_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_tiny_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..3febef7e46e9ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_bert_tiny_uncased_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_tiny_uncased_pipeline pipeline BertSentenceEmbeddings from gaunernst
+author: John Snow Labs
+name: sent_bert_tiny_uncased_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_tiny_uncased_pipeline` is a English model originally trained by gaunernst.
+
+{:.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/sent_bert_tiny_uncased_pipeline_en_5.5.0_3.0_1725355346810.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_tiny_uncased_pipeline_en_5.5.0_3.0_1725355346810.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
+
+pipeline = PretrainedPipeline("sent_bert_tiny_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_tiny_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_tiny_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|17.2 MB|
+
+## References
+
+https://huggingface.co/gaunernst/bert-tiny-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_fairlex_fscs_minilm_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-03-sent_fairlex_fscs_minilm_pipeline_de.md
new file mode 100644
index 00000000000000..05cc61e2aa4962
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_fairlex_fscs_minilm_pipeline_de.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: German sent_fairlex_fscs_minilm_pipeline pipeline XlmRoBertaSentenceEmbeddings from coastalcph
+author: John Snow Labs
+name: sent_fairlex_fscs_minilm_pipeline
+date: 2024-09-03
+tags: [de, open_source, pipeline, onnx]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_fairlex_fscs_minilm_pipeline` is a German model originally trained by coastalcph.
+
+{:.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/sent_fairlex_fscs_minilm_pipeline_de_5.5.0_3.0_1725334721289.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_fairlex_fscs_minilm_pipeline_de_5.5.0_3.0_1725334721289.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
+
+pipeline = PretrainedPipeline("sent_fairlex_fscs_minilm_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_fairlex_fscs_minilm_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_fairlex_fscs_minilm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|403.5 MB|
+
+## References
+
+https://huggingface.co/coastalcph/fairlex-fscs-minilm
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_xlmberttest_en.md b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_xlmberttest_en.md
new file mode 100644
index 00000000000000..41bef2cea9e9f8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sent_xlm_roberta_base_xlmberttest_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_xlmberttest XlmRoBertaSentenceEmbeddings from JungHun
+author: John Snow Labs
+name: sent_xlm_roberta_base_xlmberttest
+date: 2024-09-03
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+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.`sent_xlm_roberta_base_xlmberttest` is a English model originally trained by JungHun.
+
+{:.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/sent_xlm_roberta_base_xlmberttest_en_5.5.0_3.0_1725397800429.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_xlmberttest_en_5.5.0_3.0_1725397800429.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_xlmberttest","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_xlmberttest","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_xlmberttest|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|893.7 MB|
+
+## References
+
+https://huggingface.co/JungHun/xlm-roberta-base-xlmberttest
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-sentiment_analysis_italian_it.md b/docs/_posts/ahmedlone127/2024-09-03-sentiment_analysis_italian_it.md
new file mode 100644
index 00000000000000..91dfcd424d03ab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-sentiment_analysis_italian_it.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Italian sentiment_analysis_italian CamemBertForSequenceClassification from Taraassss
+author: John Snow Labs
+name: sentiment_analysis_italian
+date: 2024-09-03
+tags: [it, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: it
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_analysis_italian` is a Italian model originally trained by Taraassss.
+
+{:.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/sentiment_analysis_italian_it_5.5.0_3.0_1725325662361.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_analysis_italian_it_5.5.0_3.0_1725325662361.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("sentiment_analysis_italian","it") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("sentiment_analysis_italian", "it")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_analysis_italian|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|it|
+|Size:|394.8 MB|
+
+## References
+
+https://huggingface.co/Taraassss/sentiment_analysis_IT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-splade_v3_distilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-03-splade_v3_distilbert_pipeline_en.md
new file mode 100644
index 00000000000000..5c09d4f924b496
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-splade_v3_distilbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English splade_v3_distilbert_pipeline pipeline DistilBertEmbeddings from naver
+author: John Snow Labs
+name: splade_v3_distilbert_pipeline
+date: 2024-09-03
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`splade_v3_distilbert_pipeline` is a English model originally trained by naver.
+
+{:.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/splade_v3_distilbert_pipeline_en_5.5.0_3.0_1725384704039.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/splade_v3_distilbert_pipeline_en_5.5.0_3.0_1725384704039.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
+
+pipeline = PretrainedPipeline("splade_v3_distilbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("splade_v3_distilbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|splade_v3_distilbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/naver/splade-v3-distilbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_addi_german_xlm_r_de.md b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_addi_german_xlm_r_de.md
new file mode 100644
index 00000000000000..f3d754d8369559
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-03-xlm_roberta_qa_addi_german_xlm_r_de.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: German xlm_roberta_qa_addi_german_xlm_r XlmRoBertaForQuestionAnswering from Gantenbein
+author: John Snow Labs
+name: xlm_roberta_qa_addi_german_xlm_r
+date: 2024-09-03
+tags: [de, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_addi_german_xlm_r` is a German model originally trained by Gantenbein.
+
+{:.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/xlm_roberta_qa_addi_german_xlm_r_de_5.5.0_3.0_1725380181817.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_addi_german_xlm_r_de_5.5.0_3.0_1725380181817.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_addi_german_xlm_r","de") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_qa_addi_german_xlm_r", "de")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_addi_german_xlm_r|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|de|
+|Size:|778.0 MB|
+
+## References
+
+https://huggingface.co/Gantenbein/ADDI-DE-XLM-R
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-7_shot_sta_freezed_body_1e_5_batch_8_en.md b/docs/_posts/ahmedlone127/2024-09-04-7_shot_sta_freezed_body_1e_5_batch_8_en.md
new file mode 100644
index 00000000000000..e3a404e17c67f2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-7_shot_sta_freezed_body_1e_5_batch_8_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English 7_shot_sta_freezed_body_1e_5_batch_8 MPNetEmbeddings from Nhat1904
+author: John Snow Labs
+name: 7_shot_sta_freezed_body_1e_5_batch_8
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`7_shot_sta_freezed_body_1e_5_batch_8` is a English model originally trained by Nhat1904.
+
+{:.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/7_shot_sta_freezed_body_1e_5_batch_8_en_5.5.0_3.0_1725470363225.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/7_shot_sta_freezed_body_1e_5_batch_8_en_5.5.0_3.0_1725470363225.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("7_shot_sta_freezed_body_1e_5_batch_8","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("7_shot_sta_freezed_body_1e_5_batch_8","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|7_shot_sta_freezed_body_1e_5_batch_8|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.0 MB|
+
+## References
+
+https://huggingface.co/Nhat1904/7_shot_STA_freezed_body_1e-5_batch_8
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-akai_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-akai_ner_pipeline_en.md
new file mode 100644
index 00000000000000..ce5ab5774ebb79
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-akai_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English akai_ner_pipeline pipeline DistilBertForTokenClassification from enigma-112
+author: John Snow Labs
+name: akai_ner_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`akai_ner_pipeline` is a English model originally trained by enigma-112.
+
+{:.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/akai_ner_pipeline_en_5.5.0_3.0_1725449044094.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/akai_ner_pipeline_en_5.5.0_3.0_1725449044094.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
+
+pipeline = PretrainedPipeline("akai_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("akai_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|akai_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/enigma-112/akai_ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-albert_base_v2_finetuned_ner_minhminh09_en.md b/docs/_posts/ahmedlone127/2024-09-04-albert_base_v2_finetuned_ner_minhminh09_en.md
new file mode 100644
index 00000000000000..9284675156eed0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-albert_base_v2_finetuned_ner_minhminh09_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English albert_base_v2_finetuned_ner_minhminh09 AlbertForTokenClassification from MinhMinh09
+author: John Snow Labs
+name: albert_base_v2_finetuned_ner_minhminh09
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, albert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_v2_finetuned_ner_minhminh09` is a English model originally trained by MinhMinh09.
+
+{:.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/albert_base_v2_finetuned_ner_minhminh09_en_5.5.0_3.0_1725487144312.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_v2_finetuned_ner_minhminh09_en_5.5.0_3.0_1725487144312.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = AlbertForTokenClassification.pretrained("albert_base_v2_finetuned_ner_minhminh09","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = AlbertForTokenClassification.pretrained("albert_base_v2_finetuned_ner_minhminh09", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_v2_finetuned_ner_minhminh09|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|42.0 MB|
+
+## References
+
+https://huggingface.co/MinhMinh09/albert-base-v2-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-albert_japanese_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-albert_japanese_v2_pipeline_en.md
new file mode 100644
index 00000000000000..a40f8d3e1dd86b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-albert_japanese_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English albert_japanese_v2_pipeline pipeline AlbertEmbeddings from ALINEAR
+author: John Snow Labs
+name: albert_japanese_v2_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_japanese_v2_pipeline` is a English model originally trained by ALINEAR.
+
+{:.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/albert_japanese_v2_pipeline_en_5.5.0_3.0_1725457775349.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_japanese_v2_pipeline_en_5.5.0_3.0_1725457775349.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
+
+pipeline = PretrainedPipeline("albert_japanese_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_japanese_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_japanese_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|42.9 MB|
+
+## References
+
+https://huggingface.co/ALINEAR/albert-japanese-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-babyberta_wikipedia1_2_5_with_masking_run3_finetuned_qamr_en.md b/docs/_posts/ahmedlone127/2024-09-04-babyberta_wikipedia1_2_5_with_masking_run3_finetuned_qamr_en.md
new file mode 100644
index 00000000000000..e65e5e118c7df4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-babyberta_wikipedia1_2_5_with_masking_run3_finetuned_qamr_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English babyberta_wikipedia1_2_5_with_masking_run3_finetuned_qamr RoBertaForQuestionAnswering from lielbin
+author: John Snow Labs
+name: babyberta_wikipedia1_2_5_with_masking_run3_finetuned_qamr
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`babyberta_wikipedia1_2_5_with_masking_run3_finetuned_qamr` is a English model originally trained by lielbin.
+
+{:.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/babyberta_wikipedia1_2_5_with_masking_run3_finetuned_qamr_en_5.5.0_3.0_1725484325996.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/babyberta_wikipedia1_2_5_with_masking_run3_finetuned_qamr_en_5.5.0_3.0_1725484325996.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("babyberta_wikipedia1_2_5_with_masking_run3_finetuned_qamr","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("babyberta_wikipedia1_2_5_with_masking_run3_finetuned_qamr", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|babyberta_wikipedia1_2_5_with_masking_run3_finetuned_qamr|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|32.0 MB|
+
+## References
+
+https://huggingface.co/lielbin/BabyBERTa-Wikipedia1_2.5-with-Masking_run3-finetuned-QAMR
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-babyberta_wikipedia_2_5_0_1_finetuned_qamr_en.md b/docs/_posts/ahmedlone127/2024-09-04-babyberta_wikipedia_2_5_0_1_finetuned_qamr_en.md
new file mode 100644
index 00000000000000..fd0b846f91331f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-babyberta_wikipedia_2_5_0_1_finetuned_qamr_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English babyberta_wikipedia_2_5_0_1_finetuned_qamr RoBertaForQuestionAnswering from lielbin
+author: John Snow Labs
+name: babyberta_wikipedia_2_5_0_1_finetuned_qamr
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`babyberta_wikipedia_2_5_0_1_finetuned_qamr` is a English model originally trained by lielbin.
+
+{:.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/babyberta_wikipedia_2_5_0_1_finetuned_qamr_en_5.5.0_3.0_1725483361736.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/babyberta_wikipedia_2_5_0_1_finetuned_qamr_en_5.5.0_3.0_1725483361736.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("babyberta_wikipedia_2_5_0_1_finetuned_qamr","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("babyberta_wikipedia_2_5_0_1_finetuned_qamr", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|babyberta_wikipedia_2_5_0_1_finetuned_qamr|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|32.0 MB|
+
+## References
+
+https://huggingface.co/lielbin/babyberta-Wikipedia_2.5-0.1-finetuned-QAMR
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bert_classifier_spanish_news_classification_headlines_untrained_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-04-bert_classifier_spanish_news_classification_headlines_untrained_pipeline_es.md
new file mode 100644
index 00000000000000..6ba8bfef82c653
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bert_classifier_spanish_news_classification_headlines_untrained_pipeline_es.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Castilian, Spanish bert_classifier_spanish_news_classification_headlines_untrained_pipeline pipeline BertForSequenceClassification from M47Labs
+author: John Snow Labs
+name: bert_classifier_spanish_news_classification_headlines_untrained_pipeline
+date: 2024-09-04
+tags: [es, open_source, pipeline, onnx]
+task: Text Classification
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_spanish_news_classification_headlines_untrained_pipeline` is a Castilian, Spanish model originally trained by M47Labs.
+
+{:.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/bert_classifier_spanish_news_classification_headlines_untrained_pipeline_es_5.5.0_3.0_1725432544663.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_spanish_news_classification_headlines_untrained_pipeline_es_5.5.0_3.0_1725432544663.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
+
+pipeline = PretrainedPipeline("bert_classifier_spanish_news_classification_headlines_untrained_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_classifier_spanish_news_classification_headlines_untrained_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_classifier_spanish_news_classification_headlines_untrained_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|411.8 MB|
+
+## References
+
+https://huggingface.co/M47Labs/spanish_news_classification_headlines_untrained
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bert_sequence_classifier_coronabert_en.md b/docs/_posts/ahmedlone127/2024-09-04-bert_sequence_classifier_coronabert_en.md
new file mode 100644
index 00000000000000..f4fa2c24a7a21b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bert_sequence_classifier_coronabert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_sequence_classifier_coronabert BertForSequenceClassification from jakelever
+author: John Snow Labs
+name: bert_sequence_classifier_coronabert
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sequence_classifier_coronabert` is a English model originally trained by jakelever.
+
+{:.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/bert_sequence_classifier_coronabert_en_5.5.0_3.0_1725433153537.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_coronabert_en_5.5.0_3.0_1725433153537.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bert_sequence_classifier_coronabert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_coronabert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_sequence_classifier_coronabert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|410.4 MB|
+
+## References
+
+https://huggingface.co/jakelever/coronabert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-bertimbau_large_ner_total_pt.md b/docs/_posts/ahmedlone127/2024-09-04-bertimbau_large_ner_total_pt.md
new file mode 100644
index 00000000000000..05f544bdaca74c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-bertimbau_large_ner_total_pt.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Portuguese bertimbau_large_ner_total BertForTokenClassification from marquesafonso
+author: John Snow Labs
+name: bertimbau_large_ner_total
+date: 2024-09-04
+tags: [pt, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: pt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertimbau_large_ner_total` is a Portuguese model originally trained by marquesafonso.
+
+{:.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/bertimbau_large_ner_total_pt_5.5.0_3.0_1725477362319.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertimbau_large_ner_total_pt_5.5.0_3.0_1725477362319.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bertimbau_large_ner_total","pt") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bertimbau_large_ner_total", "pt")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bertimbau_large_ner_total|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|pt|
+|Size:|406.0 MB|
+
+## References
+
+https://huggingface.co/marquesafonso/bertimbau-large-ner-total
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_setfit_model_watwat100_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_setfit_model_watwat100_en.md
new file mode 100644
index 00000000000000..6a3dc6da4f6509
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_setfit_model_watwat100_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_setfit_model_watwat100 MPNetEmbeddings from Watwat100
+author: John Snow Labs
+name: burmese_awesome_setfit_model_watwat100
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`burmese_awesome_setfit_model_watwat100` is a English model originally trained by Watwat100.
+
+{:.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/burmese_awesome_setfit_model_watwat100_en_5.5.0_3.0_1725470390025.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_watwat100_en_5.5.0_3.0_1725470390025.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("burmese_awesome_setfit_model_watwat100","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("burmese_awesome_setfit_model_watwat100","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_setfit_model_watwat100|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/Watwat100/my-awesome-setfit-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_prbee_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_prbee_pipeline_en.md
new file mode 100644
index 00000000000000..17c7460e3e5129
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_awesome_wnut_model_prbee_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_prbee_pipeline pipeline DistilBertForTokenClassification from PrBee
+author: John Snow Labs
+name: burmese_awesome_wnut_model_prbee_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_prbee_pipeline` is a English model originally trained by PrBee.
+
+{:.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/burmese_awesome_wnut_model_prbee_pipeline_en_5.5.0_3.0_1725460667683.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_prbee_pipeline_en_5.5.0_3.0_1725460667683.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
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_prbee_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_prbee_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_prbee_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/PrBee/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_bert_qa_model_05_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_bert_qa_model_05_en.md
new file mode 100644
index 00000000000000..15b4d9ca3b1e13
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_bert_qa_model_05_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_bert_qa_model_05 RoBertaForQuestionAnswering from arunkarthik
+author: John Snow Labs
+name: burmese_bert_qa_model_05
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_bert_qa_model_05` is a English model originally trained by arunkarthik.
+
+{:.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/burmese_bert_qa_model_05_en_5.5.0_3.0_1725479254906.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_bert_qa_model_05_en_5.5.0_3.0_1725479254906.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("burmese_bert_qa_model_05","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("burmese_bert_qa_model_05", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_bert_qa_model_05|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|463.5 MB|
+
+## References
+
+https://huggingface.co/arunkarthik/my_bert_qa_model_05
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-burmese_ner_model_luccaaug_en.md b/docs/_posts/ahmedlone127/2024-09-04-burmese_ner_model_luccaaug_en.md
new file mode 100644
index 00000000000000..e0b724cfa637ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-burmese_ner_model_luccaaug_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_ner_model_luccaaug DistilBertForTokenClassification from LuccaAug
+author: John Snow Labs
+name: burmese_ner_model_luccaaug
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_ner_model_luccaaug` is a English model originally trained by LuccaAug.
+
+{:.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/burmese_ner_model_luccaaug_en_5.5.0_3.0_1725492917609.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_ner_model_luccaaug_en_5.5.0_3.0_1725492917609.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_ner_model_luccaaug","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_ner_model_luccaaug", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_ner_model_luccaaug|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/LuccaAug/my_ner_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-car_sentiment_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-car_sentiment_pipeline_en.md
new file mode 100644
index 00000000000000..9d1789e7862707
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-car_sentiment_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English car_sentiment_pipeline pipeline DistilBertForSequenceClassification from af41
+author: John Snow Labs
+name: car_sentiment_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`car_sentiment_pipeline` is a English model originally trained by af41.
+
+{:.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/car_sentiment_pipeline_en_5.5.0_3.0_1725489517093.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/car_sentiment_pipeline_en_5.5.0_3.0_1725489517093.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
+
+pipeline = PretrainedPipeline("car_sentiment_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("car_sentiment_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|car_sentiment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/af41/car_sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-clip_crop_disease_en.md b/docs/_posts/ahmedlone127/2024-09-04-clip_crop_disease_en.md
new file mode 100644
index 00000000000000..aeb5d370c23f6b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-clip_crop_disease_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English clip_crop_disease CLIPForZeroShotClassification from TonyStarkD99
+author: John Snow Labs
+name: clip_crop_disease
+date: 2024-09-04
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_crop_disease` is a English model originally trained by TonyStarkD99.
+
+{:.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/clip_crop_disease_en_5.5.0_3.0_1725492220392.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_crop_disease_en_5.5.0_3.0_1725492220392.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
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("clip_crop_disease","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_crop_disease","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_crop_disease|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|400.5 MB|
+
+## References
+
+https://huggingface.co/TonyStarkD99/CLIP-Crop_Disease
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-clip_vit_base_patch32_demo_rvignav_en.md b/docs/_posts/ahmedlone127/2024-09-04-clip_vit_base_patch32_demo_rvignav_en.md
new file mode 100644
index 00000000000000..4e1febf889e9fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-clip_vit_base_patch32_demo_rvignav_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English clip_vit_base_patch32_demo_rvignav CLIPForZeroShotClassification from rvignav
+author: John Snow Labs
+name: clip_vit_base_patch32_demo_rvignav
+date: 2024-09-04
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_vit_base_patch32_demo_rvignav` is a English model originally trained by rvignav.
+
+{:.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/clip_vit_base_patch32_demo_rvignav_en_5.5.0_3.0_1725491577175.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_vit_base_patch32_demo_rvignav_en_5.5.0_3.0_1725491577175.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
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_base_patch32_demo_rvignav","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_vit_base_patch32_demo_rvignav","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_vit_base_patch32_demo_rvignav|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|397.5 MB|
+
+## References
+
+https://huggingface.co/rvignav/clip-vit-base-patch32-demo
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-cold_fusion_itr13_seed2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-cold_fusion_itr13_seed2_pipeline_en.md
new file mode 100644
index 00000000000000..da1d45a5cf8c20
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-cold_fusion_itr13_seed2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cold_fusion_itr13_seed2_pipeline pipeline RoBertaForSequenceClassification from ibm
+author: John Snow Labs
+name: cold_fusion_itr13_seed2_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cold_fusion_itr13_seed2_pipeline` is a English model originally trained by ibm.
+
+{:.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/cold_fusion_itr13_seed2_pipeline_en_5.5.0_3.0_1725485138224.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cold_fusion_itr13_seed2_pipeline_en_5.5.0_3.0_1725485138224.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
+
+pipeline = PretrainedPipeline("cold_fusion_itr13_seed2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cold_fusion_itr13_seed2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cold_fusion_itr13_seed2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|467.9 MB|
+
+## References
+
+https://huggingface.co/ibm/ColD-Fusion-itr13-seed2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v2_large_conll2003_inca_v1_latin_fe_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v2_large_conll2003_inca_v1_latin_fe_v1_pipeline_en.md
new file mode 100644
index 00000000000000..0b25569928e73e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v2_large_conll2003_inca_v1_latin_fe_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v2_large_conll2003_inca_v1_latin_fe_v1_pipeline pipeline DeBertaForTokenClassification from Yanis
+author: John Snow Labs
+name: deberta_v2_large_conll2003_inca_v1_latin_fe_v1_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v2_large_conll2003_inca_v1_latin_fe_v1_pipeline` is a English model originally trained by Yanis.
+
+{:.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/deberta_v2_large_conll2003_inca_v1_latin_fe_v1_pipeline_en_5.5.0_3.0_1725475217785.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v2_large_conll2003_inca_v1_latin_fe_v1_pipeline_en_5.5.0_3.0_1725475217785.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
+
+pipeline = PretrainedPipeline("deberta_v2_large_conll2003_inca_v1_latin_fe_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v2_large_conll2003_inca_v1_latin_fe_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v2_large_conll2003_inca_v1_latin_fe_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/Yanis/deberta-v2-large-conll2003-inca-v1-la-fe-v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_ad_opentag_finetuned_ner_5epochs_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_ad_opentag_finetuned_ner_5epochs_pipeline_en.md
new file mode 100644
index 00000000000000..43541da054e08e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_ad_opentag_finetuned_ner_5epochs_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_large_ad_opentag_finetuned_ner_5epochs_pipeline pipeline DeBertaForTokenClassification from ABrinkmann
+author: John Snow Labs
+name: deberta_v3_large_ad_opentag_finetuned_ner_5epochs_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_ad_opentag_finetuned_ner_5epochs_pipeline` is a English model originally trained by ABrinkmann.
+
+{:.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/deberta_v3_large_ad_opentag_finetuned_ner_5epochs_pipeline_en_5.5.0_3.0_1725473147685.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_ad_opentag_finetuned_ner_5epochs_pipeline_en_5.5.0_3.0_1725473147685.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
+
+pipeline = PretrainedPipeline("deberta_v3_large_ad_opentag_finetuned_ner_5epochs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large_ad_opentag_finetuned_ner_5epochs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_ad_opentag_finetuned_ner_5epochs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/ABrinkmann/deberta-v3-large-ad-opentag-finetuned-ner-5epochs
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_finetuned_ner_10epochs_v2_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_finetuned_ner_10epochs_v2_en.md
new file mode 100644
index 00000000000000..d669a8547675a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_large_finetuned_ner_10epochs_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_large_finetuned_ner_10epochs_v2 DeBertaForTokenClassification from ABrinkmann
+author: John Snow Labs
+name: deberta_v3_large_finetuned_ner_10epochs_v2
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_finetuned_ner_10epochs_v2` is a English model originally trained by ABrinkmann.
+
+{:.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/deberta_v3_large_finetuned_ner_10epochs_v2_en_5.5.0_3.0_1725474443876.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_ner_10epochs_v2_en_5.5.0_3.0_1725474443876.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("deberta_v3_large_finetuned_ner_10epochs_v2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_large_finetuned_ner_10epochs_v2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_finetuned_ner_10epochs_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/ABrinkmann/deberta-v3-large-finetuned-ner-10epochs-V2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_ner_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_ner_v1_pipeline_en.md
new file mode 100644
index 00000000000000..db47681f903847
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-deberta_v3_ner_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_ner_v1_pipeline pipeline DeBertaForTokenClassification from kabir5297
+author: John Snow Labs
+name: deberta_v3_ner_v1_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_ner_v1_pipeline` is a English model originally trained by kabir5297.
+
+{:.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/deberta_v3_ner_v1_pipeline_en_5.5.0_3.0_1725472054520.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_ner_v1_pipeline_en_5.5.0_3.0_1725472054520.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
+
+pipeline = PretrainedPipeline("deberta_v3_ner_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_ner_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_ner_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|635.2 MB|
+
+## References
+
+https://huggingface.co/kabir5297/deberta_v3_ner_v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-delivery_balanced_distilbert_base_uncased_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-delivery_balanced_distilbert_base_uncased_v2_pipeline_en.md
new file mode 100644
index 00000000000000..0f25cfb8befa82
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-delivery_balanced_distilbert_base_uncased_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English delivery_balanced_distilbert_base_uncased_v2_pipeline pipeline DistilBertForSequenceClassification from chuuhtetnaing
+author: John Snow Labs
+name: delivery_balanced_distilbert_base_uncased_v2_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`delivery_balanced_distilbert_base_uncased_v2_pipeline` is a English model originally trained by chuuhtetnaing.
+
+{:.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/delivery_balanced_distilbert_base_uncased_v2_pipeline_en_5.5.0_3.0_1725489519536.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/delivery_balanced_distilbert_base_uncased_v2_pipeline_en_5.5.0_3.0_1725489519536.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
+
+pipeline = PretrainedPipeline("delivery_balanced_distilbert_base_uncased_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("delivery_balanced_distilbert_base_uncased_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|delivery_balanced_distilbert_base_uncased_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/chuuhtetnaing/delivery-balanced-distilbert-base-uncased-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-disbert_finetune_for_gentriple_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-disbert_finetune_for_gentriple_pipeline_en.md
new file mode 100644
index 00000000000000..4b12097c1232a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-disbert_finetune_for_gentriple_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English disbert_finetune_for_gentriple_pipeline pipeline DistilBertForTokenClassification from Malcolmcjj13
+author: John Snow Labs
+name: disbert_finetune_for_gentriple_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`disbert_finetune_for_gentriple_pipeline` is a English model originally trained by Malcolmcjj13.
+
+{:.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/disbert_finetune_for_gentriple_pipeline_en_5.5.0_3.0_1725475772628.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/disbert_finetune_for_gentriple_pipeline_en_5.5.0_3.0_1725475772628.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
+
+pipeline = PretrainedPipeline("disbert_finetune_for_gentriple_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("disbert_finetune_for_gentriple_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|disbert_finetune_for_gentriple_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/Malcolmcjj13/_disbert_finetune_for_gentriple
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_clinc_einsteinkim_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_clinc_einsteinkim_pipeline_en.md
new file mode 100644
index 00000000000000..cf471c293845f4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_clinc_einsteinkim_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_clinc_einsteinkim_pipeline pipeline DistilBertForSequenceClassification from EinsteinKim
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_clinc_einsteinkim_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_clinc_einsteinkim_pipeline` is a English model originally trained by EinsteinKim.
+
+{:.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/distilbert_base_uncased_finetuned_clinc_einsteinkim_pipeline_en_5.5.0_3.0_1725490076473.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_clinc_einsteinkim_pipeline_en_5.5.0_3.0_1725490076473.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_clinc_einsteinkim_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_clinc_einsteinkim_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_clinc_einsteinkim_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.9 MB|
+
+## References
+
+https://huggingface.co/EinsteinKim/distilbert-base-uncased-finetuned-clinc
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_emotion_wzy1924561588_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_emotion_wzy1924561588_en.md
new file mode 100644
index 00000000000000..1d48809800506a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_emotion_wzy1924561588_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_wzy1924561588 DistilBertForSequenceClassification from WzY1924561588
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_wzy1924561588
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_wzy1924561588` is a English model originally trained by WzY1924561588.
+
+{:.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/distilbert_base_uncased_finetuned_emotion_wzy1924561588_en_5.5.0_3.0_1725489504656.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_wzy1924561588_en_5.5.0_3.0_1725489504656.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_wzy1924561588","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_wzy1924561588", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_wzy1924561588|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/WzY1924561588/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_layath_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_layath_en.md
new file mode 100644
index 00000000000000..468ddf70b895fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_finetuned_ner_layath_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_layath DistilBertForTokenClassification from layath
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_layath
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_layath` is a English model originally trained by layath.
+
+{:.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/distilbert_base_uncased_finetuned_ner_layath_en_5.5.0_3.0_1725476168375.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_layath_en_5.5.0_3.0_1725476168375.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_layath","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_layath", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_layath|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/layath/distilbert-base-uncased-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_wwm_finetuned_imdb_accelerate_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_wwm_finetuned_imdb_accelerate_pipeline_en.md
new file mode 100644
index 00000000000000..4de8fcd9e9c594
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_base_uncased_wwm_finetuned_imdb_accelerate_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_wwm_finetuned_imdb_accelerate_pipeline pipeline DistilBertEmbeddings from alex-atelo
+author: John Snow Labs
+name: distilbert_base_uncased_wwm_finetuned_imdb_accelerate_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_wwm_finetuned_imdb_accelerate_pipeline` is a English model originally trained by alex-atelo.
+
+{:.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/distilbert_base_uncased_wwm_finetuned_imdb_accelerate_pipeline_en_5.5.0_3.0_1725418644945.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_wwm_finetuned_imdb_accelerate_pipeline_en_5.5.0_3.0_1725418644945.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_wwm_finetuned_imdb_accelerate_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_wwm_finetuned_imdb_accelerate_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_wwm_finetuned_imdb_accelerate_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/alex-atelo/distilbert-base-uncased-wwm-finetuned-imdb-accelerate
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-distilbert_turkish_sentiment_analysis2_en.md b/docs/_posts/ahmedlone127/2024-09-04-distilbert_turkish_sentiment_analysis2_en.md
new file mode 100644
index 00000000000000..45c101aabf8b92
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-distilbert_turkish_sentiment_analysis2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_turkish_sentiment_analysis2 DistilBertForSequenceClassification from balciberin
+author: John Snow Labs
+name: distilbert_turkish_sentiment_analysis2
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_turkish_sentiment_analysis2` is a English model originally trained by balciberin.
+
+{:.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/distilbert_turkish_sentiment_analysis2_en_5.5.0_3.0_1725490238532.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_turkish_sentiment_analysis2_en_5.5.0_3.0_1725490238532.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_turkish_sentiment_analysis2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_turkish_sentiment_analysis2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_turkish_sentiment_analysis2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/balciberin/distilbert_turkish_sentiment_analysis2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model8_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model8_en.md
new file mode 100644
index 00000000000000..abee046348076d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model8_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model8 CamemBertEmbeddings from Turka
+author: John Snow Labs
+name: dummy_model8
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model8` is a English model originally trained by Turka.
+
+{:.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/dummy_model8_en_5.5.0_3.0_1725444942304.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model8_en_5.5.0_3.0_1725444942304.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model8","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model8","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model8|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Turka/dummy-model8
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_pallavi176_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_pallavi176_en.md
new file mode 100644
index 00000000000000..d03e2fa6fd1612
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_pallavi176_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_pallavi176 CamemBertEmbeddings from pallavi176
+author: John Snow Labs
+name: dummy_model_pallavi176
+date: 2024-09-04
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_pallavi176` is a English model originally trained by pallavi176.
+
+{:.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/dummy_model_pallavi176_en_5.5.0_3.0_1725408646587.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_pallavi176_en_5.5.0_3.0_1725408646587.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_pallavi176","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_pallavi176","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_pallavi176|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/pallavi176/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_rocksat_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_rocksat_pipeline_en.md
new file mode 100644
index 00000000000000..c3a68774282f23
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_rocksat_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_rocksat_pipeline pipeline CamemBertEmbeddings from rocksat
+author: John Snow Labs
+name: dummy_model_rocksat_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_rocksat_pipeline` is a English model originally trained by rocksat.
+
+{:.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/dummy_model_rocksat_pipeline_en_5.5.0_3.0_1725443988240.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_rocksat_pipeline_en_5.5.0_3.0_1725443988240.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
+
+pipeline = PretrainedPipeline("dummy_model_rocksat_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_rocksat_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_rocksat_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/rocksat/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-dummy_model_xuda77_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_xuda77_pipeline_en.md
new file mode 100644
index 00000000000000..4d066651868b19
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-dummy_model_xuda77_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_xuda77_pipeline pipeline CamemBertEmbeddings from xuda77
+author: John Snow Labs
+name: dummy_model_xuda77_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_xuda77_pipeline` is a English model originally trained by xuda77.
+
+{:.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/dummy_model_xuda77_pipeline_en_5.5.0_3.0_1725408331602.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_xuda77_pipeline_en_5.5.0_3.0_1725408331602.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
+
+pipeline = PretrainedPipeline("dummy_model_xuda77_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_xuda77_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_xuda77_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/xuda77/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-hw_intent_atis_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-hw_intent_atis_pipeline_en.md
new file mode 100644
index 00000000000000..093e9da351f6b3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-hw_intent_atis_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English hw_intent_atis_pipeline pipeline RoBertaForSequenceClassification from RaushanTurganbay
+author: John Snow Labs
+name: hw_intent_atis_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hw_intent_atis_pipeline` is a English model originally trained by RaushanTurganbay.
+
+{:.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/hw_intent_atis_pipeline_en_5.5.0_3.0_1725485030855.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hw_intent_atis_pipeline_en_5.5.0_3.0_1725485030855.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
+
+pipeline = PretrainedPipeline("hw_intent_atis_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hw_intent_atis_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hw_intent_atis_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|422.7 MB|
+
+## References
+
+https://huggingface.co/RaushanTurganbay/hw-intent-atis
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-kor_naver_ner_name_v2_1_en.md b/docs/_posts/ahmedlone127/2024-09-04-kor_naver_ner_name_v2_1_en.md
new file mode 100644
index 00000000000000..e46318cfd4f780
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-kor_naver_ner_name_v2_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English kor_naver_ner_name_v2_1 BertForTokenClassification from joon09
+author: John Snow Labs
+name: kor_naver_ner_name_v2_1
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kor_naver_ner_name_v2_1` is a English model originally trained by joon09.
+
+{:.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/kor_naver_ner_name_v2_1_en_5.5.0_3.0_1725449603647.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kor_naver_ner_name_v2_1_en_5.5.0_3.0_1725449603647.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("kor_naver_ner_name_v2_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("kor_naver_ner_name_v2_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kor_naver_ner_name_v2_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|441.2 MB|
+
+## References
+
+https://huggingface.co/joon09/kor-naver-ner-name-v2.1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_finetuned_ai4privacy_v2_en.md b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_finetuned_ai4privacy_v2_en.md
new file mode 100644
index 00000000000000..ece4fb42a6c2c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mdeberta_v3_base_finetuned_ai4privacy_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mdeberta_v3_base_finetuned_ai4privacy_v2 DeBertaForTokenClassification from Isotonic
+author: John Snow Labs
+name: mdeberta_v3_base_finetuned_ai4privacy_v2
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, deberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_finetuned_ai4privacy_v2` is a English model originally trained by Isotonic.
+
+{:.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/mdeberta_v3_base_finetuned_ai4privacy_v2_en_5.5.0_3.0_1725472870659.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_finetuned_ai4privacy_v2_en_5.5.0_3.0_1725472870659.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DeBertaForTokenClassification.pretrained("mdeberta_v3_base_finetuned_ai4privacy_v2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DeBertaForTokenClassification.pretrained("mdeberta_v3_base_finetuned_ai4privacy_v2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_finetuned_ai4privacy_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|890.7 MB|
+
+## References
+
+https://huggingface.co/Isotonic/mdeberta-v3-base_finetuned_ai4privacy_v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-mobilebert_finetuned_sayula_popoluca_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-mobilebert_finetuned_sayula_popoluca_pipeline_en.md
new file mode 100644
index 00000000000000..f7ad9332081459
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-mobilebert_finetuned_sayula_popoluca_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mobilebert_finetuned_sayula_popoluca_pipeline pipeline BertForTokenClassification from mrm8488
+author: John Snow Labs
+name: mobilebert_finetuned_sayula_popoluca_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mobilebert_finetuned_sayula_popoluca_pipeline` is a English model originally trained by mrm8488.
+
+{:.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/mobilebert_finetuned_sayula_popoluca_pipeline_en_5.5.0_3.0_1725449872615.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mobilebert_finetuned_sayula_popoluca_pipeline_en_5.5.0_3.0_1725449872615.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
+
+pipeline = PretrainedPipeline("mobilebert_finetuned_sayula_popoluca_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mobilebert_finetuned_sayula_popoluca_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mobilebert_finetuned_sayula_popoluca_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|92.6 MB|
+
+## References
+
+https://huggingface.co/mrm8488/mobilebert-finetuned-pos
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-monobert_legal_french_fr.md b/docs/_posts/ahmedlone127/2024-09-04-monobert_legal_french_fr.md
new file mode 100644
index 00000000000000..1929f0411fa9c9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-monobert_legal_french_fr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: French monobert_legal_french CamemBertForSequenceClassification from maastrichtlawtech
+author: John Snow Labs
+name: monobert_legal_french
+date: 2024-09-04
+tags: [fr, open_source, onnx, sequence_classification, camembert]
+task: Text Classification
+language: fr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`monobert_legal_french` is a French model originally trained by maastrichtlawtech.
+
+{:.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/monobert_legal_french_fr_5.5.0_3.0_1725466656009.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/monobert_legal_french_fr_5.5.0_3.0_1725466656009.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = CamemBertForSequenceClassification.pretrained("monobert_legal_french","fr") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("monobert_legal_french", "fr")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|monobert_legal_french|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|fr|
+|Size:|415.0 MB|
+
+## References
+
+https://huggingface.co/maastrichtlawtech/monobert-legal-french
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-nepal_bhasa_trained_slovak_en.md b/docs/_posts/ahmedlone127/2024-09-04-nepal_bhasa_trained_slovak_en.md
new file mode 100644
index 00000000000000..8ee706e4e3fed3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-nepal_bhasa_trained_slovak_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English nepal_bhasa_trained_slovak DistilBertForTokenClassification from annamariagnat
+author: John Snow Labs
+name: nepal_bhasa_trained_slovak
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nepal_bhasa_trained_slovak` is a English model originally trained by annamariagnat.
+
+{:.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/nepal_bhasa_trained_slovak_en_5.5.0_3.0_1725460905191.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nepal_bhasa_trained_slovak_en_5.5.0_3.0_1725460905191.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("nepal_bhasa_trained_slovak","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("nepal_bhasa_trained_slovak", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nepal_bhasa_trained_slovak|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/annamariagnat/NEW_trained_slovak
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-ner_distilbert_classifier_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-ner_distilbert_classifier_1_pipeline_en.md
new file mode 100644
index 00000000000000..83480a4c3991d2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-ner_distilbert_classifier_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_distilbert_classifier_1_pipeline pipeline DistilBertForTokenClassification from Maaz911
+author: John Snow Labs
+name: ner_distilbert_classifier_1_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_distilbert_classifier_1_pipeline` is a English model originally trained by Maaz911.
+
+{:.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/ner_distilbert_classifier_1_pipeline_en_5.5.0_3.0_1725460455892.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_distilbert_classifier_1_pipeline_en_5.5.0_3.0_1725460455892.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
+
+pipeline = PretrainedPipeline("ner_distilbert_classifier_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_distilbert_classifier_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_distilbert_classifier_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Maaz911/NER-distilbert-classifier-1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-ner_model_techme_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-ner_model_techme_pipeline_en.md
new file mode 100644
index 00000000000000..470a7657681ee6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-ner_model_techme_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_model_techme_pipeline pipeline DistilBertForTokenClassification from techme
+author: John Snow Labs
+name: ner_model_techme_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_model_techme_pipeline` is a English model originally trained by techme.
+
+{:.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/ner_model_techme_pipeline_en_5.5.0_3.0_1725476153243.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_model_techme_pipeline_en_5.5.0_3.0_1725476153243.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
+
+pipeline = PretrainedPipeline("ner_model_techme_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_model_techme_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_model_techme_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/techme/ner_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-openai_clip_vit_large_patch14_en.md b/docs/_posts/ahmedlone127/2024-09-04-openai_clip_vit_large_patch14_en.md
new file mode 100644
index 00000000000000..7bc6dc0ac86ef9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-openai_clip_vit_large_patch14_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English openai_clip_vit_large_patch14 CLIPForZeroShotClassification from polypo
+author: John Snow Labs
+name: openai_clip_vit_large_patch14
+date: 2024-09-04
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`openai_clip_vit_large_patch14` is a English model originally trained by polypo.
+
+{:.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/openai_clip_vit_large_patch14_en_5.5.0_3.0_1725491146822.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/openai_clip_vit_large_patch14_en_5.5.0_3.0_1725491146822.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
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("openai_clip_vit_large_patch14","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("openai_clip_vit_large_patch14","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|openai_clip_vit_large_patch14|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/polypo/openai-clip-vit-large-patch14
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-pharma_classification_en.md b/docs/_posts/ahmedlone127/2024-09-04-pharma_classification_en.md
new file mode 100644
index 00000000000000..0528e2d77c449d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-pharma_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English pharma_classification DistilBertForSequenceClassification from skylord
+author: John Snow Labs
+name: pharma_classification
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pharma_classification` is a English model originally trained by skylord.
+
+{:.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/pharma_classification_en_5.5.0_3.0_1725489611573.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pharma_classification_en_5.5.0_3.0_1725489611573.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("pharma_classification","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("pharma_classification", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pharma_classification|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/skylord/pharma_classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-rise_ner_distilbert_base_cased_system_a_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-rise_ner_distilbert_base_cased_system_a_v1_pipeline_en.md
new file mode 100644
index 00000000000000..5546ac72c02010
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-rise_ner_distilbert_base_cased_system_a_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English rise_ner_distilbert_base_cased_system_a_v1_pipeline pipeline DistilBertForTokenClassification from petersamoaa
+author: John Snow Labs
+name: rise_ner_distilbert_base_cased_system_a_v1_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rise_ner_distilbert_base_cased_system_a_v1_pipeline` is a English model originally trained by petersamoaa.
+
+{:.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/rise_ner_distilbert_base_cased_system_a_v1_pipeline_en_5.5.0_3.0_1725492713798.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rise_ner_distilbert_base_cased_system_a_v1_pipeline_en_5.5.0_3.0_1725492713798.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
+
+pipeline = PretrainedPipeline("rise_ner_distilbert_base_cased_system_a_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rise_ner_distilbert_base_cased_system_a_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rise_ner_distilbert_base_cased_system_a_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.9 MB|
+
+## References
+
+https://huggingface.co/petersamoaa/rise-ner-distilbert-base-cased-system-a-v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_base_bne_finetuned_suicide_spanish_es.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_bne_finetuned_suicide_spanish_es.md
new file mode 100644
index 00000000000000..02d2e52edc541b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_bne_finetuned_suicide_spanish_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish roberta_base_bne_finetuned_suicide_spanish RoBertaForSequenceClassification from somosnlp-hackathon-2023
+author: John Snow Labs
+name: roberta_base_bne_finetuned_suicide_spanish
+date: 2024-09-04
+tags: [es, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_bne_finetuned_suicide_spanish` is a Castilian, Spanish model originally trained by somosnlp-hackathon-2023.
+
+{:.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/roberta_base_bne_finetuned_suicide_spanish_es_5.5.0_3.0_1725452442049.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_bne_finetuned_suicide_spanish_es_5.5.0_3.0_1725452442049.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta_base_bne_finetuned_suicide_spanish","es") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_bne_finetuned_suicide_spanish", "es")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_bne_finetuned_suicide_spanish|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|es|
+|Size:|437.9 MB|
+
+## References
+
+https://huggingface.co/somosnlp-hackathon-2023/roberta-base-bne-finetuned-suicide-es
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_base_squad2_finetuned_roberta_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_squad2_finetuned_roberta_pipeline_en.md
new file mode 100644
index 00000000000000..b419941e6331b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_base_squad2_finetuned_roberta_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_base_squad2_finetuned_roberta_pipeline pipeline RoBertaForQuestionAnswering from srirammadduri-ts
+author: John Snow Labs
+name: roberta_base_squad2_finetuned_roberta_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_squad2_finetuned_roberta_pipeline` is a English model originally trained by srirammadduri-ts.
+
+{:.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/roberta_base_squad2_finetuned_roberta_pipeline_en_5.5.0_3.0_1725480128982.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_squad2_finetuned_roberta_pipeline_en_5.5.0_3.0_1725480128982.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
+
+pipeline = PretrainedPipeline("roberta_base_squad2_finetuned_roberta_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_squad2_finetuned_roberta_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_squad2_finetuned_roberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.6 MB|
+
+## References
+
+https://huggingface.co/srirammadduri-ts/roberta-base-squad2-finetuned-roberta
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_human_label_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_human_label_en.md
new file mode 100644
index 00000000000000..978d0ed624972a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_human_label_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_human_label RoBertaForSequenceClassification from Multiperspective
+author: John Snow Labs
+name: roberta_human_label
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_human_label` is a English model originally trained by Multiperspective.
+
+{:.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/roberta_human_label_en_5.5.0_3.0_1725452249183.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_human_label_en_5.5.0_3.0_1725452249183.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta_human_label","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_human_label", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_human_label|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Multiperspective/roberta-human-label
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_TestQaV1_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_TestQaV1_en.md
new file mode 100644
index 00000000000000..484f8b50a12837
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_TestQaV1_en.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering (from Andranik)
+author: John Snow Labs
+name: roberta_qa_TestQaV1
+date: 2024-09-04
+tags: [en, open_source, question_answering, roberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `TestQaV1` is a English model originally trained by `Andranik`.
+
+## 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/roberta_qa_TestQaV1_en_5.5.0_3.0_1725479299425.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_TestQaV1_en_5.5.0_3.0_1725479299425.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 = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_TestQaV1","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = RoBertaForQuestionAnswering
+.pretrained("roberta_qa_TestQaV1","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.roberta.by_Andranik").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_TestQaV1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|463.5 MB|
+
+## References
+
+References
+
+- https://huggingface.co/Andranik/TestQaV1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_large_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_large_squad_pipeline_en.md
new file mode 100644
index 00000000000000..02462c000d0e23
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-roberta_qa_large_squad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_large_squad_pipeline pipeline RoBertaForQuestionAnswering from susghosh
+author: John Snow Labs
+name: roberta_qa_large_squad_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_large_squad_pipeline` is a English model originally trained by susghosh.
+
+{:.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/roberta_qa_large_squad_pipeline_en_5.5.0_3.0_1725451100184.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_large_squad_pipeline_en_5.5.0_3.0_1725451100184.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
+
+pipeline = PretrainedPipeline("roberta_qa_large_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_large_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_large_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/susghosh/roberta-large-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_MetaKD_v1_pt.md b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_MetaKD_v1_pt.md
new file mode 100644
index 00000000000000..129fdf6b19e101
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_MetaKD_v1_pt.md
@@ -0,0 +1,80 @@
+---
+layout: model
+title: Portuguese Legal BERT Sentence Embedding Large Cased model
+author: John Snow Labs
+name: sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_MetaKD_v1
+date: 2024-09-04
+tags: [bert, pt, embeddings, sentence, open_source, onnx]
+task: Embeddings
+language: pt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Legal BERT Sentence Embedding model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-large-portuguese-cased-legal-tsdae-gpl-nli-sts-MetaKD-v1` is a Portuguese model originally trained by `stjiris`.
+
+## 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/sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_MetaKD_v1_pt_5.5.0_3.0_1725454256937.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_MetaKD_v1_pt_5.5.0_3.0_1725454256937.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
+sent_embeddings = BertSentenceEmbeddings.pretrained("sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_MetaKD_v1", "pt") \
+  .setInputCols("sentence") \
+  .setOutputCol("bert_sentence")
+
+  nlp_pipeline = Pipeline(stages=[document_assembler, sentence_detector, sent_embeddings ])
+    result = pipeline.fit(data).transform(data)
+```
+```scala
+val sent_embeddings = BertSentenceEmbeddings.pretrained("sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_MetaKD_v1", "pt")
+  .setInputCols("sentence")
+  .setOutputCol("bert_sentence")
+
+  val pipeline = new Pipeline().setStages(Array(document_assembler, sentence_detector, sent_embeddings ))
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_bert_large_portuguese_cased_legal_tsdae_gpl_nli_sts_MetaKD_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|pt|
+|Size:|1.2 GB|
+
+## References
+
+References
+
+- https://huggingface.co/stjiris/bert-large-portuguese-cased-legal-tsdae-gpl-nli-sts-MetaKD-v1
+- https://github.com/rufimelo99/metadata-knowledge-distillation
+- https://github.com/rufimelo99
+- https://rufimelo99.github.io/SemanticSearchSystemForSTJ/
+- https://www.SBERT.net
+- https://www.inesc-id.pt/projects/PR07005/
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_jmedroberta_base_sentencepiece_pipeline_ja.md b/docs/_posts/ahmedlone127/2024-09-04-sent_jmedroberta_base_sentencepiece_pipeline_ja.md
new file mode 100644
index 00000000000000..b24fd361f17349
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_jmedroberta_base_sentencepiece_pipeline_ja.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Japanese sent_jmedroberta_base_sentencepiece_pipeline pipeline BertSentenceEmbeddings from alabnii
+author: John Snow Labs
+name: sent_jmedroberta_base_sentencepiece_pipeline
+date: 2024-09-04
+tags: [ja, open_source, pipeline, onnx]
+task: Embeddings
+language: ja
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_jmedroberta_base_sentencepiece_pipeline` is a Japanese model originally trained by alabnii.
+
+{:.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/sent_jmedroberta_base_sentencepiece_pipeline_ja_5.5.0_3.0_1725416102026.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_jmedroberta_base_sentencepiece_pipeline_ja_5.5.0_3.0_1725416102026.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
+
+pipeline = PretrainedPipeline("sent_jmedroberta_base_sentencepiece_pipeline", lang = "ja")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_jmedroberta_base_sentencepiece_pipeline", lang = "ja")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_jmedroberta_base_sentencepiece_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ja|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/alabnii/jmedroberta-base-sentencepiece
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_patentbert_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_patentbert_en.md
new file mode 100644
index 00000000000000..f0acd82a2c907c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_patentbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_patentbert BertSentenceEmbeddings from dheerajpai
+author: John Snow Labs
+name: sent_patentbert
+date: 2024-09-04
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_patentbert` is a English model originally trained by dheerajpai.
+
+{:.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/sent_patentbert_en_5.5.0_3.0_1725454168065.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_patentbert_en_5.5.0_3.0_1725454168065.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_patentbert","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_patentbert","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_patentbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|75.3 MB|
+
+## References
+
+https://huggingface.co/dheerajpai/patentbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_roberta_base_finetuned_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_roberta_base_finetuned_english_pipeline_en.md
new file mode 100644
index 00000000000000..1f0f4ae09fe5e0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_roberta_base_finetuned_english_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_english_pipeline pipeline XlmRoBertaSentenceEmbeddings from Davlan
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_english_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_finetuned_english_pipeline` is a English model originally trained by Davlan.
+
+{:.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/sent_xlm_roberta_base_finetuned_english_pipeline_en_5.5.0_3.0_1725419720483.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_english_pipeline_en_5.5.0_3.0_1725419720483.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
+
+pipeline = PretrainedPipeline("sent_xlm_roberta_base_finetuned_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_xlm_roberta_base_finetuned_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-english
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_roberta_base_finetuned_yiddish_en.md b/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_roberta_base_finetuned_yiddish_en.md
new file mode 100644
index 00000000000000..bbaf05e12c3762
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-sent_xlm_roberta_base_finetuned_yiddish_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_yiddish XlmRoBertaSentenceEmbeddings from urieli
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_yiddish
+date: 2024-09-04
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+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.`sent_xlm_roberta_base_finetuned_yiddish` is a English model originally trained by urieli.
+
+{:.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/sent_xlm_roberta_base_finetuned_yiddish_en_5.5.0_3.0_1725420081734.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_yiddish_en_5.5.0_3.0_1725420081734.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_yiddish","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_yiddish","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_yiddish|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/urieli/xlm-roberta-base-finetuned-yiddish
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-test4_en.md b/docs/_posts/ahmedlone127/2024-09-04-test4_en.md
new file mode 100644
index 00000000000000..2dcd3ee6e677e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-test4_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English test4 DistilBertForTokenClassification from yam1ke
+author: John Snow Labs
+name: test4
+date: 2024-09-04
+tags: [bert, en, open_source, token_classification, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test4` is a English model originally trained by yam1ke.
+
+## 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/test4_en_5.5.0_3.0_1725408527213.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test4_en_5.5.0_3.0_1725408527213.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
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("documents")
+    
+    
+tokenClassifier = DistilBertForTokenClassification.pretrained("test4","en") \
+            .setInputCols(["documents","token"]) \
+            .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("embeddings")
+    
+val tokenClassifier = DistilBertForTokenClassification  
+    .pretrained("test4", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test4|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+References
+
+https://huggingface.co/yam1ke/test4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-trained_model_mzhao39_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-trained_model_mzhao39_pipeline_en.md
new file mode 100644
index 00000000000000..de19bcf6dc33d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-trained_model_mzhao39_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English trained_model_mzhao39_pipeline pipeline BertForTokenClassification from mzhao39
+author: John Snow Labs
+name: trained_model_mzhao39_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trained_model_mzhao39_pipeline` is a English model originally trained by mzhao39.
+
+{:.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/trained_model_mzhao39_pipeline_en_5.5.0_3.0_1725477796672.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trained_model_mzhao39_pipeline_en_5.5.0_3.0_1725477796672.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
+
+pipeline = PretrainedPipeline("trained_model_mzhao39_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("trained_model_mzhao39_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trained_model_mzhao39_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/mzhao39/trained_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-trust_merged_dataset_mdeberta_v3_10epoch_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-trust_merged_dataset_mdeberta_v3_10epoch_pipeline_en.md
new file mode 100644
index 00000000000000..7617b515d971af
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-trust_merged_dataset_mdeberta_v3_10epoch_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English trust_merged_dataset_mdeberta_v3_10epoch_pipeline pipeline DeBertaForSequenceClassification from luisespinosa
+author: John Snow Labs
+name: trust_merged_dataset_mdeberta_v3_10epoch_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trust_merged_dataset_mdeberta_v3_10epoch_pipeline` is a English model originally trained by luisespinosa.
+
+{:.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/trust_merged_dataset_mdeberta_v3_10epoch_pipeline_en_5.5.0_3.0_1725468095709.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trust_merged_dataset_mdeberta_v3_10epoch_pipeline_en_5.5.0_3.0_1725468095709.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
+
+pipeline = PretrainedPipeline("trust_merged_dataset_mdeberta_v3_10epoch_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("trust_merged_dataset_mdeberta_v3_10epoch_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trust_merged_dataset_mdeberta_v3_10epoch_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|822.8 MB|
+
+## References
+
+https://huggingface.co/luisespinosa/trust-merged_dataset_mdeberta-v3_10epoch
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-twitter_comment_roberta_base_indonesian_smsa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-twitter_comment_roberta_base_indonesian_smsa_pipeline_en.md
new file mode 100644
index 00000000000000..2efb1d2d9010c6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-twitter_comment_roberta_base_indonesian_smsa_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English twitter_comment_roberta_base_indonesian_smsa_pipeline pipeline RoBertaForSequenceClassification from databoks-irfan
+author: John Snow Labs
+name: twitter_comment_roberta_base_indonesian_smsa_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_comment_roberta_base_indonesian_smsa_pipeline` is a English model originally trained by databoks-irfan.
+
+{:.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/twitter_comment_roberta_base_indonesian_smsa_pipeline_en_5.5.0_3.0_1725485303851.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_comment_roberta_base_indonesian_smsa_pipeline_en_5.5.0_3.0_1725485303851.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
+
+pipeline = PretrainedPipeline("twitter_comment_roberta_base_indonesian_smsa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("twitter_comment_roberta_base_indonesian_smsa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_comment_roberta_base_indonesian_smsa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|473.2 MB|
+
+## References
+
+https://huggingface.co/databoks-irfan/twitter-comment-roberta-base-indonesian-smsa
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_r_with_transliteration_average_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_r_with_transliteration_average_pipeline_en.md
new file mode 100644
index 00000000000000..68ff58559057b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_r_with_transliteration_average_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_r_with_transliteration_average_pipeline pipeline XlmRoBertaEmbeddings from yihongLiu
+author: John Snow Labs
+name: xlm_r_with_transliteration_average_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_r_with_transliteration_average_pipeline` is a English model originally trained by yihongLiu.
+
+{:.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/xlm_r_with_transliteration_average_pipeline_en_5.5.0_3.0_1725417961191.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_r_with_transliteration_average_pipeline_en_5.5.0_3.0_1725417961191.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
+
+pipeline = PretrainedPipeline("xlm_r_with_transliteration_average_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_r_with_transliteration_average_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_r_with_transliteration_average_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|850.0 MB|
+
+## References
+
+https://huggingface.co/yihongLiu/xlm-r-with-transliteration-average
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_transll_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_transll_en.md
new file mode 100644
index 00000000000000..ac6bdb126d1dd2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_base_finetuned_panx_german_transll_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_transll XlmRoBertaForTokenClassification from TransLL
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_transll
+date: 2024-09-04
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_transll` is a English model originally trained by TransLL.
+
+{:.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/xlm_roberta_base_finetuned_panx_german_transll_en_5.5.0_3.0_1725437355211.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_transll_en_5.5.0_3.0_1725437355211.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_transll","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_transll", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_transll|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/TransLL/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_indosquadv2_1693993923_8_2e_06_0_01_5_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_indosquadv2_1693993923_8_2e_06_0_01_5_en.md
new file mode 100644
index 00000000000000..2179a607ee00de
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_indosquadv2_1693993923_8_2e_06_0_01_5_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English xlm_roberta_indosquadv2_1693993923_8_2e_06_0_01_5 XlmRoBertaForQuestionAnswering from rizquuula
+author: John Snow Labs
+name: xlm_roberta_indosquadv2_1693993923_8_2e_06_0_01_5
+date: 2024-09-04
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_indosquadv2_1693993923_8_2e_06_0_01_5` is a English model originally trained by rizquuula.
+
+{:.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/xlm_roberta_indosquadv2_1693993923_8_2e_06_0_01_5_en_5.5.0_3.0_1725483032848.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_indosquadv2_1693993923_8_2e_06_0_01_5_en_5.5.0_3.0_1725483032848.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_indosquadv2_1693993923_8_2e_06_0_01_5","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_indosquadv2_1693993923_8_2e_06_0_01_5", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_indosquadv2_1693993923_8_2e_06_0_01_5|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|818.0 MB|
+
+## References
+
+https://huggingface.co/rizquuula/XLM-RoBERTa-IndoSQuADv2_1693993923-8-2e-06-0.01-5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_qa_autonlp_roberta_base_squad2_24465517_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_qa_autonlp_roberta_base_squad2_24465517_pipeline_en.md
new file mode 100644
index 00000000000000..35fe66d66f1c1a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlm_roberta_qa_autonlp_roberta_base_squad2_24465517_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English xlm_roberta_qa_autonlp_roberta_base_squad2_24465517_pipeline pipeline XlmRoBertaForQuestionAnswering from teacookies
+author: John Snow Labs
+name: xlm_roberta_qa_autonlp_roberta_base_squad2_24465517_pipeline
+date: 2024-09-04
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_autonlp_roberta_base_squad2_24465517_pipeline` is a English model originally trained by teacookies.
+
+{:.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/xlm_roberta_qa_autonlp_roberta_base_squad2_24465517_pipeline_en_5.5.0_3.0_1725481954870.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_roberta_base_squad2_24465517_pipeline_en_5.5.0_3.0_1725481954870.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
+
+pipeline = PretrainedPipeline("xlm_roberta_qa_autonlp_roberta_base_squad2_24465517_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_qa_autonlp_roberta_base_squad2_24465517_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_autonlp_roberta_base_squad2_24465517_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|887.4 MB|
+
+## References
+
+https://huggingface.co/teacookies/autonlp-roberta-base-squad2-24465517
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlmr_english_chinese_norwegian_shuffled_orig_test1000_en.md b/docs/_posts/ahmedlone127/2024-09-04-xlmr_english_chinese_norwegian_shuffled_orig_test1000_en.md
new file mode 100644
index 00000000000000..fe532ad6afe956
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlmr_english_chinese_norwegian_shuffled_orig_test1000_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlmr_english_chinese_norwegian_shuffled_orig_test1000 XlmRoBertaForSequenceClassification from patpizio
+author: John Snow Labs
+name: xlmr_english_chinese_norwegian_shuffled_orig_test1000
+date: 2024-09-04
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_english_chinese_norwegian_shuffled_orig_test1000` is a English model originally trained by patpizio.
+
+{:.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/xlmr_english_chinese_norwegian_shuffled_orig_test1000_en_5.5.0_3.0_1725410496091.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_english_chinese_norwegian_shuffled_orig_test1000_en_5.5.0_3.0_1725410496091.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlmr_english_chinese_norwegian_shuffled_orig_test1000","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlmr_english_chinese_norwegian_shuffled_orig_test1000", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_english_chinese_norwegian_shuffled_orig_test1000|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|828.0 MB|
+
+## References
+
+https://huggingface.co/patpizio/xlmr-en-zh-no_shuffled-orig-test1000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_xlm_roberta_base_finetuned_ner_amharic_am.md b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_xlm_roberta_base_finetuned_ner_amharic_am.md
new file mode 100644
index 00000000000000..3b0f20edb972e0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-04-xlmroberta_ner_xlm_roberta_base_finetuned_ner_amharic_am.md
@@ -0,0 +1,111 @@
+---
+layout: model
+title: Amharic Named Entity Recognition (from mbeukman)
+author: John Snow Labs
+name: xlmroberta_ner_xlm_roberta_base_finetuned_ner_amharic
+date: 2024-09-04
+tags: [xlm_roberta, ner, token_classification, am, open_source, onnx]
+task: Named Entity Recognition
+language: am
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Named Entity Recognition model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-ner-amharic` is a Amharic model orginally trained by `mbeukman`.
+
+## Predicted Entities
+
+`PER`, `ORG`, `LOC`, `DATE`
+
+{:.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/xlmroberta_ner_xlm_roberta_base_finetuned_ner_amharic_am_5.5.0_3.0_1725422972226.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_xlm_roberta_base_finetuned_ner_amharic_am_5.5.0_3.0_1725422972226.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
+documentAssembler = DocumentAssembler() \
+        .setInputCol("text") \
+        .setOutputCol("document")
+
+sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")\
+       .setInputCols(["document"])\
+       .setOutputCol("sentence")
+
+tokenizer = Tokenizer() \
+    .setInputCols("sentence") \
+    .setOutputCol("token")
+
+tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_xlm_roberta_base_finetuned_ner_amharic","am") \
+    .setInputCols(["sentence", "token"]) \
+    .setOutputCol("pos")
+
+pipeline = Pipeline(stages=[documentAssembler, sentenceDetector, tokenizer, tokenClassifier])
+
+data = spark.createDataFrame([["ስካርቻ nlp እወዳለሁ"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+          .setInputCol("text") 
+          .setOutputCol("document")
+
+val sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+       .setInputCols(Array("document"))
+       .setOutputCol("sentence")
+
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("sentence"))
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_xlm_roberta_base_finetuned_ner_amharic","am") 
+    .setInputCols(Array("sentence", "token")) 
+    .setOutputCol("pos")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler,sentenceDetector, tokenizer, tokenClassifier))
+
+val data = Seq("ስካርቻ nlp እወዳለሁ").toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_xlm_roberta_base_finetuned_ner_amharic|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|am|
+|Size:|772.3 MB|
+
+## References
+
+References
+
+- https://huggingface.co/mbeukman/xlm-roberta-base-finetuned-ner-amharic
+- https://arxiv.org/abs/2103.11811
+- https://github.com/Michael-Beukman/NERTransfer
+- https://www.apache.org/licenses/LICENSE-2.0
+- https://github.com/Michael-Beukman/NERTransfer
+- h
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bert_base_cased_news_category_test_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-bert_base_cased_news_category_test_pipeline_en.md
new file mode 100644
index 00000000000000..c5be5c2cf60b3d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bert_base_cased_news_category_test_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_cased_news_category_test_pipeline pipeline DistilBertForSequenceClassification from Emily666666
+author: John Snow Labs
+name: bert_base_cased_news_category_test_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_news_category_test_pipeline` is a English model originally trained by Emily666666.
+
+{:.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/bert_base_cased_news_category_test_pipeline_en_5.5.0_3.0_1725580409741.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_news_category_test_pipeline_en_5.5.0_3.0_1725580409741.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
+
+pipeline = PretrainedPipeline("bert_base_cased_news_category_test_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_cased_news_category_test_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased_news_category_test_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Emily666666/bert-base-cased-news-category-test
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bert_base_multilingual_cased_finetuned_ner_harem_xx.md b/docs/_posts/ahmedlone127/2024-09-05-bert_base_multilingual_cased_finetuned_ner_harem_xx.md
new file mode 100644
index 00000000000000..db634dd2cb9300
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bert_base_multilingual_cased_finetuned_ner_harem_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual bert_base_multilingual_cased_finetuned_ner_harem BertForTokenClassification from GuiTap
+author: John Snow Labs
+name: bert_base_multilingual_cased_finetuned_ner_harem
+date: 2024-09-05
+tags: [xx, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_finetuned_ner_harem` is a Multilingual model originally trained by GuiTap.
+
+{:.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/bert_base_multilingual_cased_finetuned_ner_harem_xx_5.5.0_3.0_1725515865504.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_ner_harem_xx_5.5.0_3.0_1725515865504.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_base_multilingual_cased_finetuned_ner_harem","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_base_multilingual_cased_finetuned_ner_harem", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_multilingual_cased_finetuned_ner_harem|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|xx|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/GuiTap/bert-base-multilingual-cased-finetuned-ner-harem
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bert_finetuned_ner_clinical_plncmm_large_25_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-bert_finetuned_ner_clinical_plncmm_large_25_pipeline_en.md
new file mode 100644
index 00000000000000..364b6af3a1eb2a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bert_finetuned_ner_clinical_plncmm_large_25_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_clinical_plncmm_large_25_pipeline pipeline BertForTokenClassification from crisU8
+author: John Snow Labs
+name: bert_finetuned_ner_clinical_plncmm_large_25_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_clinical_plncmm_large_25_pipeline` is a English model originally trained by crisU8.
+
+{:.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/bert_finetuned_ner_clinical_plncmm_large_25_pipeline_en_5.5.0_3.0_1725511087597.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_clinical_plncmm_large_25_pipeline_en_5.5.0_3.0_1725511087597.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
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_clinical_plncmm_large_25_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_clinical_plncmm_large_25_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_clinical_plncmm_large_25_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/crisU8/bert-finetuned-ner-clinical-plncmm-large-25
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bert_token_classifier_autotrain_jobberta_23_3671398065_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-bert_token_classifier_autotrain_jobberta_23_3671398065_pipeline_en.md
new file mode 100644
index 00000000000000..6cbe2c149dbcf0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bert_token_classifier_autotrain_jobberta_23_3671398065_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_token_classifier_autotrain_jobberta_23_3671398065_pipeline pipeline BertForTokenClassification from Andrei95
+author: John Snow Labs
+name: bert_token_classifier_autotrain_jobberta_23_3671398065_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_token_classifier_autotrain_jobberta_23_3671398065_pipeline` is a English model originally trained by Andrei95.
+
+{:.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/bert_token_classifier_autotrain_jobberta_23_3671398065_pipeline_en_5.5.0_3.0_1725539095999.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_token_classifier_autotrain_jobberta_23_3671398065_pipeline_en_5.5.0_3.0_1725539095999.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
+
+pipeline = PretrainedPipeline("bert_token_classifier_autotrain_jobberta_23_3671398065_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_token_classifier_autotrain_jobberta_23_3671398065_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_token_classifier_autotrain_jobberta_23_3671398065_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/Andrei95/autotrain-jobberta-23-3671398065
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-bertimbau_base_sayula_popoluca_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-bertimbau_base_sayula_popoluca_2_pipeline_en.md
new file mode 100644
index 00000000000000..24f4b9cd65164b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-bertimbau_base_sayula_popoluca_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bertimbau_base_sayula_popoluca_2_pipeline pipeline BertForTokenClassification from LendeaViva
+author: John Snow Labs
+name: bertimbau_base_sayula_popoluca_2_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertimbau_base_sayula_popoluca_2_pipeline` is a English model originally trained by LendeaViva.
+
+{:.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/bertimbau_base_sayula_popoluca_2_pipeline_en_5.5.0_3.0_1725516191001.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertimbau_base_sayula_popoluca_2_pipeline_en_5.5.0_3.0_1725516191001.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
+
+pipeline = PretrainedPipeline("bertimbau_base_sayula_popoluca_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bertimbau_base_sayula_popoluca_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bertimbau_base_sayula_popoluca_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.0 MB|
+
+## References
+
+https://huggingface.co/LendeaViva/bertimbau_base_pos_2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_saikatkumardey_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_saikatkumardey_pipeline_en.md
new file mode 100644
index 00000000000000..dc5f7dcadc6e7c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-burmese_awesome_wnut_model_saikatkumardey_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_saikatkumardey_pipeline pipeline DistilBertForTokenClassification from saikatkumardey
+author: John Snow Labs
+name: burmese_awesome_wnut_model_saikatkumardey_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_saikatkumardey_pipeline` is a English model originally trained by saikatkumardey.
+
+{:.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/burmese_awesome_wnut_model_saikatkumardey_pipeline_en_5.5.0_3.0_1725518180081.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_saikatkumardey_pipeline_en_5.5.0_3.0_1725518180081.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
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_saikatkumardey_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_saikatkumardey_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_saikatkumardey_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/saikatkumardey/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-burmese_ner_model_rwindia_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-burmese_ner_model_rwindia_pipeline_en.md
new file mode 100644
index 00000000000000..f9f855519c77f2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-burmese_ner_model_rwindia_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_ner_model_rwindia_pipeline pipeline DistilBertForTokenClassification from rwindia
+author: John Snow Labs
+name: burmese_ner_model_rwindia_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_ner_model_rwindia_pipeline` is a English model originally trained by rwindia.
+
+{:.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/burmese_ner_model_rwindia_pipeline_en_5.5.0_3.0_1725495929844.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_ner_model_rwindia_pipeline_en_5.5.0_3.0_1725495929844.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
+
+pipeline = PretrainedPipeline("burmese_ner_model_rwindia_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_ner_model_rwindia_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_ner_model_rwindia_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/rwindia/my_ner_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-clinicalbert_full_finetuned_ner_pablo_en.md b/docs/_posts/ahmedlone127/2024-09-05-clinicalbert_full_finetuned_ner_pablo_en.md
new file mode 100644
index 00000000000000..8f8c244e97c45e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-clinicalbert_full_finetuned_ner_pablo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English clinicalbert_full_finetuned_ner_pablo DistilBertForTokenClassification from pabRomero
+author: John Snow Labs
+name: clinicalbert_full_finetuned_ner_pablo
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clinicalbert_full_finetuned_ner_pablo` is a English model originally trained by pabRomero.
+
+{:.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/clinicalbert_full_finetuned_ner_pablo_en_5.5.0_3.0_1725506375635.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clinicalbert_full_finetuned_ner_pablo_en_5.5.0_3.0_1725506375635.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("clinicalbert_full_finetuned_ner_pablo","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("clinicalbert_full_finetuned_ner_pablo", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clinicalbert_full_finetuned_ner_pablo|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/pabRomero/ClinicalBERT-full-finetuned-ner-pablo
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-clip_fine_tuned_satellite_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-clip_fine_tuned_satellite_pipeline_en.md
new file mode 100644
index 00000000000000..c3796b30a0515e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-clip_fine_tuned_satellite_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English clip_fine_tuned_satellite_pipeline pipeline CLIPForZeroShotClassification from NemesisAlm
+author: John Snow Labs
+name: clip_fine_tuned_satellite_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_fine_tuned_satellite_pipeline` is a English model originally trained by NemesisAlm.
+
+{:.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/clip_fine_tuned_satellite_pipeline_en_5.5.0_3.0_1725540191368.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_fine_tuned_satellite_pipeline_en_5.5.0_3.0_1725540191368.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
+
+pipeline = PretrainedPipeline("clip_fine_tuned_satellite_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clip_fine_tuned_satellite_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_fine_tuned_satellite_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|449.9 MB|
+
+## References
+
+https://huggingface.co/NemesisAlm/clip-fine-tuned-satellite
+
+## Included Models
+
+- ImageAssembler
+- CLIPForZeroShotClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-cpu_economywide_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-cpu_economywide_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..1f5388fa036e0a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-cpu_economywide_classifier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cpu_economywide_classifier_pipeline pipeline MPNetForSequenceClassification from mtyrrell
+author: John Snow Labs
+name: cpu_economywide_classifier_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cpu_economywide_classifier_pipeline` is a English model originally trained by mtyrrell.
+
+{:.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/cpu_economywide_classifier_pipeline_en_5.5.0_3.0_1725575627672.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cpu_economywide_classifier_pipeline_en_5.5.0_3.0_1725575627672.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
+
+pipeline = PretrainedPipeline("cpu_economywide_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cpu_economywide_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cpu_economywide_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.5 MB|
+
+## References
+
+https://huggingface.co/mtyrrell/CPU_Economywide_Classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- MPNetForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_emotion_ft_0703_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_emotion_ft_0703_en.md
new file mode 100644
index 00000000000000..d2cabbcb32d171
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_emotion_ft_0703_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_emotion_ft_0703 DistilBertForSequenceClassification from liuguojing
+author: John Snow Labs
+name: distilbert_base_uncased_emotion_ft_0703
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_emotion_ft_0703` is a English model originally trained by liuguojing.
+
+{:.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/distilbert_base_uncased_emotion_ft_0703_en_5.5.0_3.0_1725580533876.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_emotion_ft_0703_en_5.5.0_3.0_1725580533876.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_emotion_ft_0703","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_emotion_ft_0703", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_emotion_ft_0703|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/liuguojing/distilbert-base-uncased_emotion_ft_0703
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_jerrish_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_jerrish_en.md
new file mode 100644
index 00000000000000..abcfbd2b159a81
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_jerrish_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_jerrish DistilBertForTokenClassification from jerrish
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_jerrish
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_jerrish` is a English model originally trained by jerrish.
+
+{:.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/distilbert_base_uncased_finetuned_ner_jerrish_en_5.5.0_3.0_1725518181254.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_jerrish_en_5.5.0_3.0_1725518181254.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_jerrish","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_jerrish", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_jerrish|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/jerrish/distilbert-base-uncased-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_jerrish_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_jerrish_pipeline_en.md
new file mode 100644
index 00000000000000..6eaa9de489790d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_ner_jerrish_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_jerrish_pipeline pipeline DistilBertForTokenClassification from jerrish
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_jerrish_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_jerrish_pipeline` is a English model originally trained by jerrish.
+
+{:.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/distilbert_base_uncased_finetuned_ner_jerrish_pipeline_en_5.5.0_3.0_1725518193162.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_jerrish_pipeline_en_5.5.0_3.0_1725518193162.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_jerrish_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_jerrish_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_jerrish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/jerrish/distilbert-base-uncased-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_sentiment_luluw_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_sentiment_luluw_pipeline_en.md
new file mode 100644
index 00000000000000..adf196b9c3f976
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_sentiment_luluw_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_sentiment_luluw_pipeline pipeline DistilBertForSequenceClassification from luluw
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_sentiment_luluw_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_sentiment_luluw_pipeline` is a English model originally trained by luluw.
+
+{:.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/distilbert_base_uncased_finetuned_sentiment_luluw_pipeline_en_5.5.0_3.0_1725580521793.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_sentiment_luluw_pipeline_en_5.5.0_3.0_1725580521793.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_sentiment_luluw_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_sentiment_luluw_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_sentiment_luluw_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/luluw/distilbert-base-uncased-finetuned-sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_srl_jing1113_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_srl_jing1113_en.md
new file mode 100644
index 00000000000000..1838dd41f449e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_base_uncased_finetuned_srl_jing1113_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_srl_jing1113 DistilBertForTokenClassification from Jing1113
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_srl_jing1113
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_srl_jing1113` is a English model originally trained by Jing1113.
+
+{:.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/distilbert_base_uncased_finetuned_srl_jing1113_en_5.5.0_3.0_1725506030747.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_srl_jing1113_en_5.5.0_3.0_1725506030747.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_srl_jing1113","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_srl_jing1113", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_srl_jing1113|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.4 MB|
+
+## References
+
+https://huggingface.co/Jing1113/distilbert-base-uncased-finetuned-srl
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_exp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_exp_pipeline_en.md
new file mode 100644
index 00000000000000..e29e29a51c9e05
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_exp_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_exp_pipeline pipeline DistilBertForSequenceClassification from BruceT02
+author: John Snow Labs
+name: distilbert_exp_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_exp_pipeline` is a English model originally trained by BruceT02.
+
+{:.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/distilbert_exp_pipeline_en_5.5.0_3.0_1725580633993.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_exp_pipeline_en_5.5.0_3.0_1725580633993.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
+
+pipeline = PretrainedPipeline("distilbert_exp_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_exp_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_exp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/BruceT02/DistilBert_Exp
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_imdb_padding40model_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_imdb_padding40model_en.md
new file mode 100644
index 00000000000000..36fec3cc880f6d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_imdb_padding40model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_imdb_padding40model DistilBertForSequenceClassification from Realgon
+author: John Snow Labs
+name: distilbert_imdb_padding40model
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_imdb_padding40model` is a English model originally trained by Realgon.
+
+{:.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/distilbert_imdb_padding40model_en_5.5.0_3.0_1725507771000.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_imdb_padding40model_en_5.5.0_3.0_1725507771000.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_imdb_padding40model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_imdb_padding40model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_imdb_padding40model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Realgon/distilbert_imdb_padding40model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distilbert_v0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-distilbert_v0_pipeline_en.md
new file mode 100644
index 00000000000000..97d89873fd95aa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distilbert_v0_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_v0_pipeline pipeline DistilBertForTokenClassification from labicquette
+author: John Snow Labs
+name: distilbert_v0_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_v0_pipeline` is a English model originally trained by labicquette.
+
+{:.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/distilbert_v0_pipeline_en_5.5.0_3.0_1725518701173.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_v0_pipeline_en_5.5.0_3.0_1725518701173.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
+
+pipeline = PretrainedPipeline("distilbert_v0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_v0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_v0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/labicquette/distilbert-v0
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-distillbert_base_ner_pii200_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-distillbert_base_ner_pii200_pipeline_en.md
new file mode 100644
index 00000000000000..be3305570e4d8a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-distillbert_base_ner_pii200_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distillbert_base_ner_pii200_pipeline pipeline DistilBertForTokenClassification from vuminhtue
+author: John Snow Labs
+name: distillbert_base_ner_pii200_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distillbert_base_ner_pii200_pipeline` is a English model originally trained by vuminhtue.
+
+{:.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/distillbert_base_ner_pii200_pipeline_en_5.5.0_3.0_1725505866553.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distillbert_base_ner_pii200_pipeline_en_5.5.0_3.0_1725505866553.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
+
+pipeline = PretrainedPipeline("distillbert_base_ner_pii200_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distillbert_base_ner_pii200_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distillbert_base_ner_pii200_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.4 MB|
+
+## References
+
+https://huggingface.co/vuminhtue/DistillBert_base_NER_PII200
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-drbert_casm2_fr.md b/docs/_posts/ahmedlone127/2024-09-05-drbert_casm2_fr.md
new file mode 100644
index 00000000000000..3e079f8323c002
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-drbert_casm2_fr.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: French drbert_casm2 BertForTokenClassification from camila-ud
+author: John Snow Labs
+name: drbert_casm2
+date: 2024-09-05
+tags: [bert, fr, open_source, token_classification, onnx]
+task: Named Entity Recognition
+language: fr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`drbert_casm2` is a French model originally trained by camila-ud.
+
+## 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/drbert_casm2_fr_5.5.0_3.0_1725563274065.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/drbert_casm2_fr_5.5.0_3.0_1725563274065.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
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("documents")
+    
+    
+tokenClassifier = BertForTokenClassification.pretrained("drbert_casm2","fr") \
+            .setInputCols(["documents","token"]) \
+            .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("embeddings")
+    
+val tokenClassifier = BertForTokenClassification  
+    .pretrained("drbert_casm2", "fr")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|drbert_casm2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|fr|
+|Size:|408.2 MB|
+
+## References
+
+References
+
+https://huggingface.co/camila-ud/DrBERT-CASM2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-fake_news_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-fake_news_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..5959e6c70c13f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-fake_news_classifier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English fake_news_classifier_pipeline pipeline RoBertaForSequenceClassification from T0asty
+author: John Snow Labs
+name: fake_news_classifier_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fake_news_classifier_pipeline` is a English model originally trained by T0asty.
+
+{:.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/fake_news_classifier_pipeline_en_5.5.0_3.0_1725542163663.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fake_news_classifier_pipeline_en_5.5.0_3.0_1725542163663.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
+
+pipeline = PretrainedPipeline("fake_news_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fake_news_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fake_news_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|461.4 MB|
+
+## References
+
+https://huggingface.co/T0asty/fake-news-classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-finetuned_iitp_pdt_review_indic_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-finetuned_iitp_pdt_review_indic_bert_pipeline_en.md
new file mode 100644
index 00000000000000..ac549f04e35be6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-finetuned_iitp_pdt_review_indic_bert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuned_iitp_pdt_review_indic_bert_pipeline pipeline AlbertForSequenceClassification from aditeyabaral
+author: John Snow Labs
+name: finetuned_iitp_pdt_review_indic_bert_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_iitp_pdt_review_indic_bert_pipeline` is a English model originally trained by aditeyabaral.
+
+{:.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/finetuned_iitp_pdt_review_indic_bert_pipeline_en_5.5.0_3.0_1725543438220.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_iitp_pdt_review_indic_bert_pipeline_en_5.5.0_3.0_1725543438220.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
+
+pipeline = PretrainedPipeline("finetuned_iitp_pdt_review_indic_bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_iitp_pdt_review_indic_bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_iitp_pdt_review_indic_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|127.8 MB|
+
+## References
+
+https://huggingface.co/aditeyabaral/finetuned-iitp_pdt_review-indic-bert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-finetuned_model_en.md b/docs/_posts/ahmedlone127/2024-09-05-finetuned_model_en.md
new file mode 100644
index 00000000000000..71a5aa9b07bdce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-finetuned_model_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English finetuned_model DistilBertForTokenClassification from hemulitch
+author: John Snow Labs
+name: finetuned_model
+date: 2024-09-05
+tags: [bert, en, open_source, token_classification, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_model` is a English model originally trained by hemulitch.
+
+## 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/finetuned_model_en_5.5.0_3.0_1725542166564.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_model_en_5.5.0_3.0_1725542166564.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
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("documents")
+    
+    
+tokenClassifier = DistilBertForTokenClassification.pretrained("finetuned_model","en") \
+            .setInputCols(["documents","token"]) \
+            .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("embeddings")
+    
+val tokenClassifier = DistilBertForTokenClassification  
+    .pretrained("finetuned_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|468.2 MB|
+
+## References
+
+References
+
+https://huggingface.co/hemulitch/finetuned_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-hate_speech_filipino_xlm_r_en.md b/docs/_posts/ahmedlone127/2024-09-05-hate_speech_filipino_xlm_r_en.md
new file mode 100644
index 00000000000000..353bd70d3d63e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-hate_speech_filipino_xlm_r_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English hate_speech_filipino_xlm_r XlmRoBertaForSequenceClassification from Cincin-nvp
+author: John Snow Labs
+name: hate_speech_filipino_xlm_r
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hate_speech_filipino_xlm_r` is a English model originally trained by Cincin-nvp.
+
+{:.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/hate_speech_filipino_xlm_r_en_5.5.0_3.0_1725526158696.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hate_speech_filipino_xlm_r_en_5.5.0_3.0_1725526158696.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("hate_speech_filipino_xlm_r","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("hate_speech_filipino_xlm_r", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hate_speech_filipino_xlm_r|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|866.4 MB|
+
+## References
+
+https://huggingface.co/Cincin-nvp/hate_speech_filipino_XLM-R
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-hw01_liamli1991_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-hw01_liamli1991_pipeline_en.md
new file mode 100644
index 00000000000000..1543a5a3c24338
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-hw01_liamli1991_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English hw01_liamli1991_pipeline pipeline DistilBertForSequenceClassification from LiamLi1991
+author: John Snow Labs
+name: hw01_liamli1991_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hw01_liamli1991_pipeline` is a English model originally trained by LiamLi1991.
+
+{:.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/hw01_liamli1991_pipeline_en_5.5.0_3.0_1725507450280.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hw01_liamli1991_pipeline_en_5.5.0_3.0_1725507450280.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
+
+pipeline = PretrainedPipeline("hw01_liamli1991_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hw01_liamli1991_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hw01_liamli1991_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LiamLi1991/HW01
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-imdbreviews_classification_distilbert_v02_sebasr0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-imdbreviews_classification_distilbert_v02_sebasr0_pipeline_en.md
new file mode 100644
index 00000000000000..b97c06f5b9181e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-imdbreviews_classification_distilbert_v02_sebasr0_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English imdbreviews_classification_distilbert_v02_sebasr0_pipeline pipeline DistilBertForSequenceClassification from sebasr0
+author: John Snow Labs
+name: imdbreviews_classification_distilbert_v02_sebasr0_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`imdbreviews_classification_distilbert_v02_sebasr0_pipeline` is a English model originally trained by sebasr0.
+
+{:.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/imdbreviews_classification_distilbert_v02_sebasr0_pipeline_en_5.5.0_3.0_1725507201502.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/imdbreviews_classification_distilbert_v02_sebasr0_pipeline_en_5.5.0_3.0_1725507201502.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
+
+pipeline = PretrainedPipeline("imdbreviews_classification_distilbert_v02_sebasr0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("imdbreviews_classification_distilbert_v02_sebasr0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|imdbreviews_classification_distilbert_v02_sebasr0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/sebasr0/imdbreviews_classification_distilbert_v02
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-incollection_recognizer_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-incollection_recognizer_pipeline_en.md
new file mode 100644
index 00000000000000..0a847219dd1c04
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-incollection_recognizer_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English incollection_recognizer_pipeline pipeline DistilBertForSequenceClassification from LaLaf93
+author: John Snow Labs
+name: incollection_recognizer_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`incollection_recognizer_pipeline` is a English model originally trained by LaLaf93.
+
+{:.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/incollection_recognizer_pipeline_en_5.5.0_3.0_1725580283940.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/incollection_recognizer_pipeline_en_5.5.0_3.0_1725580283940.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
+
+pipeline = PretrainedPipeline("incollection_recognizer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("incollection_recognizer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|incollection_recognizer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LaLaf93/incollection_recognizer
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-longformer_base_4096_spanish_es.md b/docs/_posts/ahmedlone127/2024-09-05-longformer_base_4096_spanish_es.md
new file mode 100644
index 00000000000000..565edbb86f9a72
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-longformer_base_4096_spanish_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish longformer_base_4096_spanish RoBertaEmbeddings from mrm8488
+author: John Snow Labs
+name: longformer_base_4096_spanish
+date: 2024-09-05
+tags: [es, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`longformer_base_4096_spanish` is a Castilian, Spanish model originally trained by mrm8488.
+
+{:.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/longformer_base_4096_spanish_es_5.5.0_3.0_1725566278552.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/longformer_base_4096_spanish_es_5.5.0_3.0_1725566278552.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("longformer_base_4096_spanish","es") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("longformer_base_4096_spanish","es") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|longformer_base_4096_spanish|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|es|
+|Size:|472.6 MB|
+
+## References
+
+https://huggingface.co/mrm8488/longformer-base-4096-spanish
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-maltese_coref_english_french_coref_exp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-maltese_coref_english_french_coref_exp_pipeline_en.md
new file mode 100644
index 00000000000000..3b57a447a83482
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-maltese_coref_english_french_coref_exp_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English maltese_coref_english_french_coref_exp_pipeline pipeline MarianTransformer from nlphuji
+author: John Snow Labs
+name: maltese_coref_english_french_coref_exp_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`maltese_coref_english_french_coref_exp_pipeline` is a English model originally trained by nlphuji.
+
+{:.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/maltese_coref_english_french_coref_exp_pipeline_en_5.5.0_3.0_1725494405892.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/maltese_coref_english_french_coref_exp_pipeline_en_5.5.0_3.0_1725494405892.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
+
+pipeline = PretrainedPipeline("maltese_coref_english_french_coref_exp_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("maltese_coref_english_french_coref_exp_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|maltese_coref_english_french_coref_exp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|509.2 MB|
+
+## References
+
+https://huggingface.co/nlphuji/mt_coref_en_fr_coref_exp
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_magnustragardh_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_magnustragardh_pipeline_en.md
new file mode 100644
index 00000000000000..19cc53543dafd3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_magnustragardh_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_magnustragardh_pipeline pipeline MarianTransformer from magnustragardh
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_magnustragardh_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_magnustragardh_pipeline` is a English model originally trained by magnustragardh.
+
+{:.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/marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_magnustragardh_pipeline_en_5.5.0_3.0_1725545383822.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_magnustragardh_pipeline_en_5.5.0_3.0_1725545383822.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
+
+pipeline = PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_magnustragardh_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_magnustragardh_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_magnustragardh_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|508.7 MB|
+
+## References
+
+https://huggingface.co/magnustragardh/marian-finetuned-kde4-en-to-fr-accelerate
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-marian_finetuned_kde4_english_tonga_tonga_islands_french_jingyi28_en.md b/docs/_posts/ahmedlone127/2024-09-05-marian_finetuned_kde4_english_tonga_tonga_islands_french_jingyi28_en.md
new file mode 100644
index 00000000000000..8d8ed41a30757e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-marian_finetuned_kde4_english_tonga_tonga_islands_french_jingyi28_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_jingyi28 MarianTransformer from Jingyi28
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_jingyi28
+date: 2024-09-05
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_jingyi28` is a English model originally trained by Jingyi28.
+
+{:.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/marian_finetuned_kde4_english_tonga_tonga_islands_french_jingyi28_en_5.5.0_3.0_1725494846767.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_jingyi28_en_5.5.0_3.0_1725494846767.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_jingyi28","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_jingyi28","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_jingyi28|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.3 MB|
+
+## References
+
+https://huggingface.co/Jingyi28/marian-finetuned-kde4-en-to-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-medical_enes_basque_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-medical_enes_basque_pipeline_en.md
new file mode 100644
index 00000000000000..d622b6ad28c18c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-medical_enes_basque_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English medical_enes_basque_pipeline pipeline MarianTransformer from anegda
+author: John Snow Labs
+name: medical_enes_basque_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medical_enes_basque_pipeline` is a English model originally trained by anegda.
+
+{:.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/medical_enes_basque_pipeline_en_5.5.0_3.0_1725545490502.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medical_enes_basque_pipeline_en_5.5.0_3.0_1725545490502.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
+
+pipeline = PretrainedPipeline("medical_enes_basque_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("medical_enes_basque_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|medical_enes_basque_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|137.7 MB|
+
+## References
+
+https://huggingface.co/anegda/medical_enes-eu
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-medidalroberta_en.md b/docs/_posts/ahmedlone127/2024-09-05-medidalroberta_en.md
new file mode 100644
index 00000000000000..6f01ee539c6ce2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-medidalroberta_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English medidalroberta XlmRoBertaForSequenceClassification from achDev
+author: John Snow Labs
+name: medidalroberta
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medidalroberta` is a English model originally trained by achDev.
+
+{:.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/medidalroberta_en_5.5.0_3.0_1725535859707.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medidalroberta_en_5.5.0_3.0_1725535859707.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("medidalroberta","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("medidalroberta", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|medidalroberta|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|797.5 MB|
+
+## References
+
+https://huggingface.co/achDev/medidalRoberta
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-mpnet_adaptation_mitigation_classifier_en.md b/docs/_posts/ahmedlone127/2024-09-05-mpnet_adaptation_mitigation_classifier_en.md
new file mode 100644
index 00000000000000..376cc78020f0b4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-mpnet_adaptation_mitigation_classifier_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English mpnet_adaptation_mitigation_classifier MPNetEmbeddings from ppsingh
+author: John Snow Labs
+name: mpnet_adaptation_mitigation_classifier
+date: 2024-09-05
+tags: [mpnet, en, open_source, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetForSequenceClassification
+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_adaptation_mitigation_classifier` is a English model originally trained by ppsingh.
+
+## 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_adaptation_mitigation_classifier_en_5.5.0_3.0_1725575390504.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_adaptation_mitigation_classifier_en_5.5.0_3.0_1725575390504.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_adaptation_mitigation_classifier","en") \
+            .setInputCols(["documents"]) \
+            .setOutputCol("mpnet_embeddings")
+
+pipeline = Pipeline().setStages([document_assembler, embeddings])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("documents")
+    
+val embeddings = MPNetEmbeddings 
+    .pretrained("mpnet_adaptation_mitigation_classifier", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("mpnet_embeddings") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnet_adaptation_mitigation_classifier|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.5 MB|
+
+## References
+
+References
+
+https://huggingface.co/ppsingh/mpnet-adaptation_mitigation-classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-norwegian_bokml_roberta_base_scandi_1e4_en.md b/docs/_posts/ahmedlone127/2024-09-05-norwegian_bokml_roberta_base_scandi_1e4_en.md
new file mode 100644
index 00000000000000..c4d64f04fe6e5a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-norwegian_bokml_roberta_base_scandi_1e4_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English norwegian_bokml_roberta_base_scandi_1e4 XlmRoBertaEmbeddings from NbAiLab
+author: John Snow Labs
+name: norwegian_bokml_roberta_base_scandi_1e4
+date: 2024-09-05
+tags: [en, open_source, onnx, embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norwegian_bokml_roberta_base_scandi_1e4` is a English model originally trained by NbAiLab.
+
+{:.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/norwegian_bokml_roberta_base_scandi_1e4_en_5.5.0_3.0_1725555650109.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norwegian_bokml_roberta_base_scandi_1e4_en_5.5.0_3.0_1725555650109.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = XlmRoBertaEmbeddings.pretrained("norwegian_bokml_roberta_base_scandi_1e4","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = XlmRoBertaEmbeddings.pretrained("norwegian_bokml_roberta_base_scandi_1e4","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|norwegian_bokml_roberta_base_scandi_1e4|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[xlm_roberta]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/NbAiLab/nb-roberta-base-scandi-1e4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-norwegian_intent_classifier_model2_no.md b/docs/_posts/ahmedlone127/2024-09-05-norwegian_intent_classifier_model2_no.md
new file mode 100644
index 00000000000000..c17370eaed9f1a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-norwegian_intent_classifier_model2_no.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Norwegian norwegian_intent_classifier_model2 DistilBertForSequenceClassification from Mukalingam0813
+author: John Snow Labs
+name: norwegian_intent_classifier_model2
+date: 2024-09-05
+tags: ["no", open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: "no"
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norwegian_intent_classifier_model2` is a Norwegian model originally trained by Mukalingam0813.
+
+{:.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/norwegian_intent_classifier_model2_no_5.5.0_3.0_1725580616271.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norwegian_intent_classifier_model2_no_5.5.0_3.0_1725580616271.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("norwegian_intent_classifier_model2","no") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("norwegian_intent_classifier_model2", "no")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|norwegian_intent_classifier_model2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|no|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/Mukalingam0813/Norwegian-intent-classifier-model2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-pll_model_en.md b/docs/_posts/ahmedlone127/2024-09-05-pll_model_en.md
new file mode 100644
index 00000000000000..5740fcb944ae82
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-pll_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English pll_model DistilBertForTokenClassification from Yaroslavbud
+author: John Snow Labs
+name: pll_model
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pll_model` is a English model originally trained by Yaroslavbud.
+
+{:.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/pll_model_en_5.5.0_3.0_1725495801835.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pll_model_en_5.5.0_3.0_1725495801835.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("pll_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("pll_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pll_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Yaroslavbud/PLL_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-predicting_misdirection_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-predicting_misdirection_pipeline_en.md
new file mode 100644
index 00000000000000..86ae0b69bc4177
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-predicting_misdirection_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English predicting_misdirection_pipeline pipeline DistilBertForSequenceClassification from Eappelson
+author: John Snow Labs
+name: predicting_misdirection_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`predicting_misdirection_pipeline` is a English model originally trained by Eappelson.
+
+{:.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/predicting_misdirection_pipeline_en_5.5.0_3.0_1725507797643.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/predicting_misdirection_pipeline_en_5.5.0_3.0_1725507797643.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
+
+pipeline = PretrainedPipeline("predicting_misdirection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("predicting_misdirection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|predicting_misdirection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Eappelson/predicting_misdirection
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-pubchem10m_smiles_bpe_120k_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-pubchem10m_smiles_bpe_120k_pipeline_en.md
new file mode 100644
index 00000000000000..c472d2f1dca68b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-pubchem10m_smiles_bpe_120k_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English pubchem10m_smiles_bpe_120k_pipeline pipeline RoBertaEmbeddings from seyonec
+author: John Snow Labs
+name: pubchem10m_smiles_bpe_120k_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pubchem10m_smiles_bpe_120k_pipeline` is a English model originally trained by seyonec.
+
+{:.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/pubchem10m_smiles_bpe_120k_pipeline_en_5.5.0_3.0_1725565836849.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pubchem10m_smiles_bpe_120k_pipeline_en_5.5.0_3.0_1725565836849.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
+
+pipeline = PretrainedPipeline("pubchem10m_smiles_bpe_120k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("pubchem10m_smiles_bpe_120k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pubchem10m_smiles_bpe_120k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|310.9 MB|
+
+## References
+
+https://huggingface.co/seyonec/PubChem10M_SMILES_BPE_120k
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-reward_model_deberta_v3_unit_test_en.md b/docs/_posts/ahmedlone127/2024-09-05-reward_model_deberta_v3_unit_test_en.md
new file mode 100644
index 00000000000000..b719b42e97e50f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-reward_model_deberta_v3_unit_test_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English reward_model_deberta_v3_unit_test DeBertaForSequenceClassification from MaxJeblick
+author: John Snow Labs
+name: reward_model_deberta_v3_unit_test
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`reward_model_deberta_v3_unit_test` is a English model originally trained by MaxJeblick.
+
+{:.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/reward_model_deberta_v3_unit_test_en_5.5.0_3.0_1725562395220.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/reward_model_deberta_v3_unit_test_en_5.5.0_3.0_1725562395220.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("reward_model_deberta_v3_unit_test","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("reward_model_deberta_v3_unit_test", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|reward_model_deberta_v3_unit_test|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|7.0 MB|
+
+## References
+
+https://huggingface.co/MaxJeblick/reward-model-deberta-v3-unit-test
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-roberta_base_epoch_52_en.md b/docs/_posts/ahmedlone127/2024-09-05-roberta_base_epoch_52_en.md
new file mode 100644
index 00000000000000..106ee4212c1f24
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-roberta_base_epoch_52_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_epoch_52 RoBertaEmbeddings from yanaiela
+author: John Snow Labs
+name: roberta_base_epoch_52
+date: 2024-09-05
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_epoch_52` is a English model originally trained by yanaiela.
+
+{:.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/roberta_base_epoch_52_en_5.5.0_3.0_1725577513482.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_epoch_52_en_5.5.0_3.0_1725577513482.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_base_epoch_52","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_base_epoch_52","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_epoch_52|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|297.3 MB|
+
+## References
+
+https://huggingface.co/yanaiela/roberta-base-epoch_52
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-roberta_base_epoch_75_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-roberta_base_epoch_75_pipeline_en.md
new file mode 100644
index 00000000000000..40646ad34ddf3a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-roberta_base_epoch_75_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_epoch_75_pipeline pipeline RoBertaEmbeddings from yanaiela
+author: John Snow Labs
+name: roberta_base_epoch_75_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_epoch_75_pipeline` is a English model originally trained by yanaiela.
+
+{:.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/roberta_base_epoch_75_pipeline_en_5.5.0_3.0_1725577602578.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_epoch_75_pipeline_en_5.5.0_3.0_1725577602578.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
+
+pipeline = PretrainedPipeline("roberta_base_epoch_75_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_epoch_75_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_epoch_75_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|297.3 MB|
+
+## References
+
+https://huggingface.co/yanaiela/roberta-base-epoch_75
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-roberta_qa_movie_roberta_MITmovie_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-roberta_qa_movie_roberta_MITmovie_squad_pipeline_en.md
new file mode 100644
index 00000000000000..b8e7a925748b06
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-roberta_qa_movie_roberta_MITmovie_squad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_movie_roberta_MITmovie_squad_pipeline pipeline RoBertaForQuestionAnswering from thatdramebaazguy
+author: John Snow Labs
+name: roberta_qa_movie_roberta_MITmovie_squad_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_movie_roberta_MITmovie_squad_pipeline` is a English model originally trained by thatdramebaazguy.
+
+{:.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/roberta_qa_movie_roberta_MITmovie_squad_pipeline_en_5.5.0_3.0_1725576115125.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_movie_roberta_MITmovie_squad_pipeline_en_5.5.0_3.0_1725576115125.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
+
+pipeline = PretrainedPipeline("roberta_qa_movie_roberta_MITmovie_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_movie_roberta_MITmovie_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_movie_roberta_MITmovie_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.0 MB|
+
+## References
+
+https://huggingface.co/thatdramebaazguy/movie-roberta-MITmovie-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-samind_sentiment_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-samind_sentiment_pipeline_en.md
new file mode 100644
index 00000000000000..580e6c85b1faae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-samind_sentiment_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English samind_sentiment_pipeline pipeline XlmRoBertaForSequenceClassification from woranit
+author: John Snow Labs
+name: samind_sentiment_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`samind_sentiment_pipeline` is a English model originally trained by woranit.
+
+{:.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/samind_sentiment_pipeline_en_5.5.0_3.0_1725537338021.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/samind_sentiment_pipeline_en_5.5.0_3.0_1725537338021.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
+
+pipeline = PretrainedPipeline("samind_sentiment_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("samind_sentiment_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|samind_sentiment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|826.3 MB|
+
+## References
+
+https://huggingface.co/woranit/samind-sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sent_bert_large_uncased_whole_word_masking_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-sent_bert_large_uncased_whole_word_masking_pipeline_en.md
new file mode 100644
index 00000000000000..98751ca9beaaf9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sent_bert_large_uncased_whole_word_masking_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_large_uncased_whole_word_masking_pipeline pipeline BertSentenceEmbeddings from google-bert
+author: John Snow Labs
+name: sent_bert_large_uncased_whole_word_masking_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_large_uncased_whole_word_masking_pipeline` is a English model originally trained by google-bert.
+
+{:.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/sent_bert_large_uncased_whole_word_masking_pipeline_en_5.5.0_3.0_1725520812678.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_large_uncased_whole_word_masking_pipeline_en_5.5.0_3.0_1725520812678.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
+
+pipeline = PretrainedPipeline("sent_bert_large_uncased_whole_word_masking_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_large_uncased_whole_word_masking_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_large_uncased_whole_word_masking_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/google-bert/bert-large-uncased-whole-word-masking
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sent_xlm_roberta_base_finetuned_chichewa_en.md b/docs/_posts/ahmedlone127/2024-09-05-sent_xlm_roberta_base_finetuned_chichewa_en.md
new file mode 100644
index 00000000000000..cc4dbe0c4bf9f4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sent_xlm_roberta_base_finetuned_chichewa_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_chichewa XlmRoBertaSentenceEmbeddings from Davlan
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_chichewa
+date: 2024-09-05
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+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.`sent_xlm_roberta_base_finetuned_chichewa` is a English model originally trained by Davlan.
+
+{:.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/sent_xlm_roberta_base_finetuned_chichewa_en_5.5.0_3.0_1725504366252.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_chichewa_en_5.5.0_3.0_1725504366252.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_chichewa","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_chichewa","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_chichewa|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-chichewa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-sept_1_2024_awesome_eli5_mlm_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-sept_1_2024_awesome_eli5_mlm_model_pipeline_en.md
new file mode 100644
index 00000000000000..eb8f05ec63133a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-sept_1_2024_awesome_eli5_mlm_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sept_1_2024_awesome_eli5_mlm_model_pipeline pipeline RoBertaEmbeddings from jzkv5
+author: John Snow Labs
+name: sept_1_2024_awesome_eli5_mlm_model_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sept_1_2024_awesome_eli5_mlm_model_pipeline` is a English model originally trained by jzkv5.
+
+{:.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/sept_1_2024_awesome_eli5_mlm_model_pipeline_en_5.5.0_3.0_1725572695091.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sept_1_2024_awesome_eli5_mlm_model_pipeline_en_5.5.0_3.0_1725572695091.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
+
+pipeline = PretrainedPipeline("sept_1_2024_awesome_eli5_mlm_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sept_1_2024_awesome_eli5_mlm_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sept_1_2024_awesome_eli5_mlm_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.5 MB|
+
+## References
+
+https://huggingface.co/jzkv5/Sept_1_2024_awesome_eli5_mlm_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-spanish_english_all_copy_quy_en.md b/docs/_posts/ahmedlone127/2024-09-05-spanish_english_all_copy_quy_en.md
new file mode 100644
index 00000000000000..99c97ba345d7bb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-spanish_english_all_copy_quy_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English spanish_english_all_copy_quy MarianTransformer from nouman-10
+author: John Snow Labs
+name: spanish_english_all_copy_quy
+date: 2024-09-05
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spanish_english_all_copy_quy` is a English model originally trained by nouman-10.
+
+{:.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/spanish_english_all_copy_quy_en_5.5.0_3.0_1725544723703.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spanish_english_all_copy_quy_en_5.5.0_3.0_1725544723703.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("spanish_english_all_copy_quy","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("spanish_english_all_copy_quy","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|spanish_english_all_copy_quy|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|539.3 MB|
+
+## References
+
+https://huggingface.co/nouman-10/es_en_all_copy_quy
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-trained_croatian_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-trained_croatian_pipeline_en.md
new file mode 100644
index 00000000000000..15714525d33101
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-trained_croatian_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English trained_croatian_pipeline pipeline DistilBertForTokenClassification from annamariagnat
+author: John Snow Labs
+name: trained_croatian_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trained_croatian_pipeline` is a English model originally trained by annamariagnat.
+
+{:.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/trained_croatian_pipeline_en_5.5.0_3.0_1725495711933.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trained_croatian_pipeline_en_5.5.0_3.0_1725495711933.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
+
+pipeline = PretrainedPipeline("trained_croatian_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("trained_croatian_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trained_croatian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/annamariagnat/trained_croatian
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-translation_model_hansollll_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-translation_model_hansollll_pipeline_en.md
new file mode 100644
index 00000000000000..5fcc1bb6ed091d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-translation_model_hansollll_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English translation_model_hansollll_pipeline pipeline MarianTransformer from Hansollll
+author: John Snow Labs
+name: translation_model_hansollll_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`translation_model_hansollll_pipeline` is a English model originally trained by Hansollll.
+
+{:.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/translation_model_hansollll_pipeline_en_5.5.0_3.0_1725545657863.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/translation_model_hansollll_pipeline_en_5.5.0_3.0_1725545657863.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
+
+pipeline = PretrainedPipeline("translation_model_hansollll_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("translation_model_hansollll_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|translation_model_hansollll_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|541.1 MB|
+
+## References
+
+https://huggingface.co/Hansollll/translation_model
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-tuning_lr_2e_05_wd_0_1_en.md b/docs/_posts/ahmedlone127/2024-09-05-tuning_lr_2e_05_wd_0_1_en.md
new file mode 100644
index 00000000000000..cbb882ad121f0d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-tuning_lr_2e_05_wd_0_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English tuning_lr_2e_05_wd_0_1 DistilBertForSequenceClassification from ash-akjp-ga
+author: John Snow Labs
+name: tuning_lr_2e_05_wd_0_1
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tuning_lr_2e_05_wd_0_1` is a English model originally trained by ash-akjp-ga.
+
+{:.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/tuning_lr_2e_05_wd_0_1_en_5.5.0_3.0_1725580382947.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tuning_lr_2e_05_wd_0_1_en_5.5.0_3.0_1725580382947.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("tuning_lr_2e_05_wd_0_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("tuning_lr_2e_05_wd_0_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tuning_lr_2e_05_wd_0_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ash-akjp-ga/tuning_lr_2e-05_wd_0.1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-twitter_roberta_base_2019_90m_en.md b/docs/_posts/ahmedlone127/2024-09-05-twitter_roberta_base_2019_90m_en.md
new file mode 100644
index 00000000000000..ccbb1a8ecd0723
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-twitter_roberta_base_2019_90m_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English twitter_roberta_base_2019_90m RoBertaEmbeddings from cardiffnlp
+author: John Snow Labs
+name: twitter_roberta_base_2019_90m
+date: 2024-09-05
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_base_2019_90m` is a English model originally trained by cardiffnlp.
+
+{:.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/twitter_roberta_base_2019_90m_en_5.5.0_3.0_1725573048326.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_2019_90m_en_5.5.0_3.0_1725573048326.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("twitter_roberta_base_2019_90m","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("twitter_roberta_base_2019_90m","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_roberta_base_2019_90m|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/cardiffnlp/twitter-roberta-base-2019-90m
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-twitter_roberta_base_2021_124m_irony_en.md b/docs/_posts/ahmedlone127/2024-09-05-twitter_roberta_base_2021_124m_irony_en.md
new file mode 100644
index 00000000000000..22d46e68d049ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-twitter_roberta_base_2021_124m_irony_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English twitter_roberta_base_2021_124m_irony RoBertaForSequenceClassification from cardiffnlp
+author: John Snow Labs
+name: twitter_roberta_base_2021_124m_irony
+date: 2024-09-05
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_base_2021_124m_irony` is a English model originally trained by cardiffnlp.
+
+{:.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/twitter_roberta_base_2021_124m_irony_en_5.5.0_3.0_1725541532552.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_2021_124m_irony_en_5.5.0_3.0_1725541532552.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("twitter_roberta_base_2021_124m_irony","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("twitter_roberta_base_2021_124m_irony", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_roberta_base_2021_124m_irony|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|468.3 MB|
+
+## References
+
+https://huggingface.co/cardiffnlp/twitter-roberta-base-2021-124m-irony
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-wg_bert_en.md b/docs/_posts/ahmedlone127/2024-09-05-wg_bert_en.md
new file mode 100644
index 00000000000000..cec8aa496f970f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-wg_bert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English wg_bert BertForTokenClassification from lukasweber
+author: John Snow Labs
+name: wg_bert
+date: 2024-09-05
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wg_bert` is a English model originally trained by lukasweber.
+
+{:.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/wg_bert_en_5.5.0_3.0_1725516287538.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wg_bert_en_5.5.0_3.0_1725516287538.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("wg_bert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("wg_bert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|wg_bert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/lukasweber/WG_BERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265897_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265897_pipeline_en.md
new file mode 100644
index 00000000000000..7347904b9d9102
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265897_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265897_pipeline pipeline XlmRoBertaForQuestionAnswering from teacookies
+author: John Snow Labs
+name: xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265897_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265897_pipeline` is a English model originally trained by teacookies.
+
+{:.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/xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265897_pipeline_en_5.5.0_3.0_1725499581954.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265897_pipeline_en_5.5.0_3.0_1725499581954.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
+
+pipeline = PretrainedPipeline("xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265897_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265897_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_qa_autonlp_more_fine_tune_24465520_26265897_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|888.2 MB|
+
+## References
+
+https://huggingface.co/teacookies/autonlp-more_fine_tune_24465520-26265897
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-xlmr_english_german_all_shuffled_764_test1000_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-xlmr_english_german_all_shuffled_764_test1000_pipeline_en.md
new file mode 100644
index 00000000000000..4bea3c41adfcb6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-xlmr_english_german_all_shuffled_764_test1000_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlmr_english_german_all_shuffled_764_test1000_pipeline pipeline XlmRoBertaForSequenceClassification from patpizio
+author: John Snow Labs
+name: xlmr_english_german_all_shuffled_764_test1000_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_english_german_all_shuffled_764_test1000_pipeline` is a English model originally trained by patpizio.
+
+{:.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/xlmr_english_german_all_shuffled_764_test1000_pipeline_en_5.5.0_3.0_1725537683650.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_english_german_all_shuffled_764_test1000_pipeline_en_5.5.0_3.0_1725537683650.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
+
+pipeline = PretrainedPipeline("xlmr_english_german_all_shuffled_764_test1000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmr_english_german_all_shuffled_764_test1000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_english_german_all_shuffled_764_test1000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|826.3 MB|
+
+## References
+
+https://huggingface.co/patpizio/xlmr-en-de-all_shuffled-764-test1000
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-05-yappychappy_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-05-yappychappy_pipeline_en.md
new file mode 100644
index 00000000000000..4fd976d8a6379c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-05-yappychappy_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English yappychappy_pipeline pipeline DistilBertForTokenClassification from CoRGI-HF
+author: John Snow Labs
+name: yappychappy_pipeline
+date: 2024-09-05
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yappychappy_pipeline` is a English model originally trained by CoRGI-HF.
+
+{:.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/yappychappy_pipeline_en_5.5.0_3.0_1725500818543.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yappychappy_pipeline_en_5.5.0_3.0_1725500818543.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
+
+pipeline = PretrainedPipeline("yappychappy_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("yappychappy_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|yappychappy_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|244.0 MB|
+
+## References
+
+https://huggingface.co/CoRGI-HF/YappyChappy
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-500_sdb_taxxl_truncate_768_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-500_sdb_taxxl_truncate_768_pipeline_en.md
new file mode 100644
index 00000000000000..69a8e530fc97f5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-500_sdb_taxxl_truncate_768_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English 500_sdb_taxxl_truncate_768_pipeline pipeline DistilBertEmbeddings from sripadhstudy
+author: John Snow Labs
+name: 500_sdb_taxxl_truncate_768_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`500_sdb_taxxl_truncate_768_pipeline` is a English model originally trained by sripadhstudy.
+
+{:.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/500_sdb_taxxl_truncate_768_pipeline_en_5.5.0_3.0_1725639289497.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/500_sdb_taxxl_truncate_768_pipeline_en_5.5.0_3.0_1725639289497.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
+
+pipeline = PretrainedPipeline("500_sdb_taxxl_truncate_768_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("500_sdb_taxxl_truncate_768_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|500_sdb_taxxl_truncate_768_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.6 MB|
+
+## References
+
+https://huggingface.co/sripadhstudy/500_SDB_TAxxL_truncate_768
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-accu_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-accu_2_pipeline_en.md
new file mode 100644
index 00000000000000..fa08ceb422349f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-accu_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English accu_2_pipeline pipeline RoBertaForSequenceClassification from BaronSch
+author: John Snow Labs
+name: accu_2_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`accu_2_pipeline` is a English model originally trained by BaronSch.
+
+{:.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/accu_2_pipeline_en_5.5.0_3.0_1725613486979.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/accu_2_pipeline_en_5.5.0_3.0_1725613486979.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
+
+pipeline = PretrainedPipeline("accu_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("accu_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|accu_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.5 MB|
+
+## References
+
+https://huggingface.co/BaronSch/Accu_2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-ai_human_detai_pipeline_kk.md b/docs/_posts/ahmedlone127/2024-09-06-ai_human_detai_pipeline_kk.md
new file mode 100644
index 00000000000000..27c92916ad188c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-ai_human_detai_pipeline_kk.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Kazakh ai_human_detai_pipeline pipeline DistilBertForSequenceClassification from Ayanm
+author: John Snow Labs
+name: ai_human_detai_pipeline
+date: 2024-09-06
+tags: [kk, open_source, pipeline, onnx]
+task: Text Classification
+language: kk
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ai_human_detai_pipeline` is a Kazakh model originally trained by Ayanm.
+
+{:.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/ai_human_detai_pipeline_kk_5.5.0_3.0_1725608332378.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ai_human_detai_pipeline_kk_5.5.0_3.0_1725608332378.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
+
+pipeline = PretrainedPipeline("ai_human_detai_pipeline", lang = "kk")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ai_human_detai_pipeline", lang = "kk")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ai_human_detai_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|kk|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Ayanm/ai-human-detai
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-albert_base_v2_cola_textattack_en.md b/docs/_posts/ahmedlone127/2024-09-06-albert_base_v2_cola_textattack_en.md
new file mode 100644
index 00000000000000..f6043d1806e850
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-albert_base_v2_cola_textattack_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English albert_base_v2_cola_textattack AlbertForSequenceClassification from textattack
+author: John Snow Labs
+name: albert_base_v2_cola_textattack
+date: 2024-09-06
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_v2_cola_textattack` is a English model originally trained by textattack.
+
+{:.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/albert_base_v2_cola_textattack_en_5.5.0_3.0_1725661787401.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_v2_cola_textattack_en_5.5.0_3.0_1725661787401.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("albert_base_v2_cola_textattack","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("albert_base_v2_cola_textattack", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_v2_cola_textattack|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/textattack/albert-base-v2-CoLA
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-albert_base_v2_finetuned_irony_en.md b/docs/_posts/ahmedlone127/2024-09-06-albert_base_v2_finetuned_irony_en.md
new file mode 100644
index 00000000000000..492e9a22a887dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-albert_base_v2_finetuned_irony_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English albert_base_v2_finetuned_irony AlbertForSequenceClassification from niktasadr98
+author: John Snow Labs
+name: albert_base_v2_finetuned_irony
+date: 2024-09-06
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_v2_finetuned_irony` is a English model originally trained by niktasadr98.
+
+{:.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/albert_base_v2_finetuned_irony_en_5.5.0_3.0_1725662288549.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_v2_finetuned_irony_en_5.5.0_3.0_1725662288549.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("albert_base_v2_finetuned_irony","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("albert_base_v2_finetuned_irony", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_v2_finetuned_irony|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/niktasadr98/albert-base-v2-finetuned-irony
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-albert_base_v2_luciayn_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-albert_base_v2_luciayn_pipeline_en.md
new file mode 100644
index 00000000000000..0e4e794f507aae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-albert_base_v2_luciayn_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English albert_base_v2_luciayn_pipeline pipeline AlbertForSequenceClassification from luciayn
+author: John Snow Labs
+name: albert_base_v2_luciayn_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_v2_luciayn_pipeline` is a English model originally trained by luciayn.
+
+{:.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/albert_base_v2_luciayn_pipeline_en_5.5.0_3.0_1725662349932.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_v2_luciayn_pipeline_en_5.5.0_3.0_1725662349932.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
+
+pipeline = PretrainedPipeline("albert_base_v2_luciayn_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_base_v2_luciayn_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_v2_luciayn_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/luciayn/albert_base_v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-albert_bbc_news_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-albert_bbc_news_pipeline_en.md
new file mode 100644
index 00000000000000..4842d8e81c7562
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-albert_bbc_news_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English albert_bbc_news_pipeline pipeline AlbertForSequenceClassification from AyoubChLin
+author: John Snow Labs
+name: albert_bbc_news_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_bbc_news_pipeline` is a English model originally trained by AyoubChLin.
+
+{:.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/albert_bbc_news_pipeline_en_5.5.0_3.0_1725662581671.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_bbc_news_pipeline_en_5.5.0_3.0_1725662581671.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
+
+pipeline = PretrainedPipeline("albert_bbc_news_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_bbc_news_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_bbc_news_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|834.0 MB|
+
+## References
+
+https://huggingface.co/AyoubChLin/Albert-bbc-news
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-all_mpnet_128_10_mnr_portuguese_en.md b/docs/_posts/ahmedlone127/2024-09-06-all_mpnet_128_10_mnr_portuguese_en.md
new file mode 100644
index 00000000000000..08feb011bb94f3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-all_mpnet_128_10_mnr_portuguese_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English all_mpnet_128_10_mnr_portuguese MPNetEmbeddings from ronanki
+author: John Snow Labs
+name: all_mpnet_128_10_mnr_portuguese
+date: 2024-09-06
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`all_mpnet_128_10_mnr_portuguese` is a English model originally trained by ronanki.
+
+{:.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/all_mpnet_128_10_mnr_portuguese_en_5.5.0_3.0_1725595817848.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_128_10_mnr_portuguese_en_5.5.0_3.0_1725595817848.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("all_mpnet_128_10_mnr_portuguese","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("all_mpnet_128_10_mnr_portuguese","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_mpnet_128_10_mnr_portuguese|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/ronanki/all_mpnet_128_10_MNR_PT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-all_mpnet_128_10_mnr_portuguese_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-all_mpnet_128_10_mnr_portuguese_pipeline_en.md
new file mode 100644
index 00000000000000..d5828e38b2584f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-all_mpnet_128_10_mnr_portuguese_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English all_mpnet_128_10_mnr_portuguese_pipeline pipeline MPNetEmbeddings from ronanki
+author: John Snow Labs
+name: all_mpnet_128_10_mnr_portuguese_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_128_10_mnr_portuguese_pipeline` is a English model originally trained by ronanki.
+
+{:.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/all_mpnet_128_10_mnr_portuguese_pipeline_en_5.5.0_3.0_1725595838038.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_128_10_mnr_portuguese_pipeline_en_5.5.0_3.0_1725595838038.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
+
+pipeline = PretrainedPipeline("all_mpnet_128_10_mnr_portuguese_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_mpnet_128_10_mnr_portuguese_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_mpnet_128_10_mnr_portuguese_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/ronanki/all_mpnet_128_10_MNR_PT
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-assistantapp_whisper_quran_ar.md b/docs/_posts/ahmedlone127/2024-09-06-assistantapp_whisper_quran_ar.md
new file mode 100644
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@@ -0,0 +1,84 @@
+---
+layout: model
+title: Arabic assistantapp_whisper_quran WhisperForCTC from AssistantApp
+author: John Snow Labs
+name: assistantapp_whisper_quran
+date: 2024-09-06
+tags: [ar, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`assistantapp_whisper_quran` is a Arabic model originally trained by AssistantApp.
+
+{:.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/assistantapp_whisper_quran_ar_5.5.0_3.0_1725603893446.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/assistantapp_whisper_quran_ar_5.5.0_3.0_1725603893446.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
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("assistantapp_whisper_quran","ar") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("assistantapp_whisper_quran", "ar")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|assistantapp_whisper_quran|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|ar|
+|Size:|643.1 MB|
+
+## References
+
+https://huggingface.co/AssistantApp/assistantapp-whisper-quran
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-atte_0_en.md b/docs/_posts/ahmedlone127/2024-09-06-atte_0_en.md
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+---
+layout: model
+title: English atte_0 RoBertaForSequenceClassification from BaronSch
+author: John Snow Labs
+name: atte_0
+date: 2024-09-06
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`atte_0` is a English model originally trained by BaronSch.
+
+{:.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/atte_0_en_5.5.0_3.0_1725613034655.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/atte_0_en_5.5.0_3.0_1725613034655.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("atte_0","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("atte_0", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|atte_0|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|468.5 MB|
+
+## References
+
+https://huggingface.co/BaronSch/Atte_0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-bert_base_german_dbmdz_uncased_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-06-bert_base_german_dbmdz_uncased_pipeline_de.md
new file mode 100644
index 00000000000000..2a12d961b7c70c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-bert_base_german_dbmdz_uncased_pipeline_de.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: German bert_base_german_dbmdz_uncased_pipeline pipeline BertEmbeddings from google-bert
+author: John Snow Labs
+name: bert_base_german_dbmdz_uncased_pipeline
+date: 2024-09-06
+tags: [de, open_source, pipeline, onnx]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_german_dbmdz_uncased_pipeline` is a German model originally trained by google-bert.
+
+{:.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/bert_base_german_dbmdz_uncased_pipeline_de_5.5.0_3.0_1725659227303.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_german_dbmdz_uncased_pipeline_de_5.5.0_3.0_1725659227303.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
+
+pipeline = PretrainedPipeline("bert_base_german_dbmdz_uncased_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_german_dbmdz_uncased_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_german_dbmdz_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|409.9 MB|
+
+## References
+
+https://huggingface.co/google-bert/bert-base-german-dbmdz-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-bert_checkpoint_980000_en.md b/docs/_posts/ahmedlone127/2024-09-06-bert_checkpoint_980000_en.md
new file mode 100644
index 00000000000000..b5b222c2ea382d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-bert_checkpoint_980000_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_checkpoint_980000 BertEmbeddings from Atipico1
+author: John Snow Labs
+name: bert_checkpoint_980000
+date: 2024-09-06
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_checkpoint_980000` is a English model originally trained by Atipico1.
+
+{:.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/bert_checkpoint_980000_en_5.5.0_3.0_1725659725535.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_checkpoint_980000_en_5.5.0_3.0_1725659725535.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_checkpoint_980000","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_checkpoint_980000","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_checkpoint_980000|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|408.2 MB|
+
+## References
+
+https://huggingface.co/Atipico1/bert-checkpoint-980000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-bert_fda_nutrition_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-bert_fda_nutrition_ner_pipeline_en.md
new file mode 100644
index 00000000000000..7ca76c0d321a6d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-bert_fda_nutrition_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_fda_nutrition_ner_pipeline pipeline BertForTokenClassification from sgarbi
+author: John Snow Labs
+name: bert_fda_nutrition_ner_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_fda_nutrition_ner_pipeline` is a English model originally trained by sgarbi.
+
+{:.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/bert_fda_nutrition_ner_pipeline_en_5.5.0_3.0_1725600626825.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_fda_nutrition_ner_pipeline_en_5.5.0_3.0_1725600626825.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
+
+pipeline = PretrainedPipeline("bert_fda_nutrition_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_fda_nutrition_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_fda_nutrition_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.3 MB|
+
+## References
+
+https://huggingface.co/sgarbi/bert-fda-nutrition-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-bert_finetuned1_squad_en.md b/docs/_posts/ahmedlone127/2024-09-06-bert_finetuned1_squad_en.md
new file mode 100644
index 00000000000000..d7dc4f368e2972
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-bert_finetuned1_squad_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_finetuned1_squad XlmRoBertaForQuestionAnswering from Echiguerkh
+author: John Snow Labs
+name: bert_finetuned1_squad
+date: 2024-09-06
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned1_squad` is a English model originally trained by Echiguerkh.
+
+{:.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/bert_finetuned1_squad_en_5.5.0_3.0_1725640806066.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned1_squad_en_5.5.0_3.0_1725640806066.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("bert_finetuned1_squad","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("bert_finetuned1_squad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned1_squad|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|794.9 MB|
+
+## References
+
+https://huggingface.co/Echiguerkh/bert-finetuned1-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-bert_ner_kriyans_en.md b/docs/_posts/ahmedlone127/2024-09-06-bert_ner_kriyans_en.md
new file mode 100644
index 00000000000000..77b5cd41f6f9f4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-bert_ner_kriyans_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_ner_kriyans BertForTokenClassification from Kriyans
+author: John Snow Labs
+name: bert_ner_kriyans
+date: 2024-09-06
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ner_kriyans` is a English model originally trained by Kriyans.
+
+{:.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/bert_ner_kriyans_en_5.5.0_3.0_1725600289997.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ner_kriyans_en_5.5.0_3.0_1725600289997.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_ner_kriyans","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_ner_kriyans", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_ner_kriyans|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/Kriyans/Bert-NER
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-bert_phishing_classifier_student_jeahyung_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-bert_phishing_classifier_student_jeahyung_pipeline_en.md
new file mode 100644
index 00000000000000..8715f5b5f95b77
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-bert_phishing_classifier_student_jeahyung_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_phishing_classifier_student_jeahyung_pipeline pipeline DistilBertForSequenceClassification from JeaHyung
+author: John Snow Labs
+name: bert_phishing_classifier_student_jeahyung_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_phishing_classifier_student_jeahyung_pipeline` is a English model originally trained by JeaHyung.
+
+{:.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/bert_phishing_classifier_student_jeahyung_pipeline_en_5.5.0_3.0_1725608448995.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_phishing_classifier_student_jeahyung_pipeline_en_5.5.0_3.0_1725608448995.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
+
+pipeline = PretrainedPipeline("bert_phishing_classifier_student_jeahyung_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_phishing_classifier_student_jeahyung_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_phishing_classifier_student_jeahyung_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|196.4 MB|
+
+## References
+
+https://huggingface.co/JeaHyung/bert-phishing-classifier_student
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-bias_classifier_roberta_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-bias_classifier_roberta_pipeline_en.md
new file mode 100644
index 00000000000000..326c70cf1f8d9c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-bias_classifier_roberta_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bias_classifier_roberta_pipeline pipeline RoBertaForSequenceClassification from wu981526092
+author: John Snow Labs
+name: bias_classifier_roberta_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bias_classifier_roberta_pipeline` is a English model originally trained by wu981526092.
+
+{:.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/bias_classifier_roberta_pipeline_en_5.5.0_3.0_1725613215904.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bias_classifier_roberta_pipeline_en_5.5.0_3.0_1725613215904.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
+
+pipeline = PretrainedPipeline("bias_classifier_roberta_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bias_classifier_roberta_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bias_classifier_roberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|457.6 MB|
+
+## References
+
+https://huggingface.co/wu981526092/bias_classifier_roberta
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_qa_model_ahmad01010101_en.md b/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_qa_model_ahmad01010101_en.md
new file mode 100644
index 00000000000000..0d5b96e96d4f30
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_qa_model_ahmad01010101_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_ahmad01010101 DistilBertForQuestionAnswering from ahmad01010101
+author: John Snow Labs
+name: burmese_awesome_qa_model_ahmad01010101
+date: 2024-09-06
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_ahmad01010101` is a English model originally trained by ahmad01010101.
+
+{:.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/burmese_awesome_qa_model_ahmad01010101_en_5.5.0_3.0_1725654928942.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_ahmad01010101_en_5.5.0_3.0_1725654928942.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_ahmad01010101","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_ahmad01010101", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_ahmad01010101|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/ahmad01010101/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_qa_model_farfalla_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_qa_model_farfalla_pipeline_en.md
new file mode 100644
index 00000000000000..17c3b439c65d49
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_qa_model_farfalla_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_farfalla_pipeline pipeline DistilBertForQuestionAnswering from farfalla
+author: John Snow Labs
+name: burmese_awesome_qa_model_farfalla_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_farfalla_pipeline` is a English model originally trained by farfalla.
+
+{:.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/burmese_awesome_qa_model_farfalla_pipeline_en_5.5.0_3.0_1725655079332.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_farfalla_pipeline_en_5.5.0_3.0_1725655079332.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_farfalla_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_farfalla_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_farfalla_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/farfalla/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_qa_model_fede_ezeq_en.md b/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_qa_model_fede_ezeq_en.md
new file mode 100644
index 00000000000000..8573cbafc96837
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_qa_model_fede_ezeq_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_fede_ezeq DistilBertForQuestionAnswering from Fede-ezeq
+author: John Snow Labs
+name: burmese_awesome_qa_model_fede_ezeq
+date: 2024-09-06
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_fede_ezeq` is a English model originally trained by Fede-ezeq.
+
+{:.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/burmese_awesome_qa_model_fede_ezeq_en_5.5.0_3.0_1725654355495.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_fede_ezeq_en_5.5.0_3.0_1725654355495.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_fede_ezeq","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_fede_ezeq", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_fede_ezeq|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|250.2 MB|
+
+## References
+
+https://huggingface.co/Fede-ezeq/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_qa_model_lizhealey_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_qa_model_lizhealey_pipeline_en.md
new file mode 100644
index 00000000000000..38681ec99d5f6e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_qa_model_lizhealey_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_lizhealey_pipeline pipeline DistilBertForQuestionAnswering from lizhealey
+author: John Snow Labs
+name: burmese_awesome_qa_model_lizhealey_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_lizhealey_pipeline` is a English model originally trained by lizhealey.
+
+{:.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/burmese_awesome_qa_model_lizhealey_pipeline_en_5.5.0_3.0_1725652687081.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_lizhealey_pipeline_en_5.5.0_3.0_1725652687081.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_lizhealey_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_lizhealey_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_lizhealey_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/lizhealey/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_qa_model_munnafaisal_en.md b/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_qa_model_munnafaisal_en.md
new file mode 100644
index 00000000000000..4f8a3f97f92af0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_qa_model_munnafaisal_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_munnafaisal DistilBertForQuestionAnswering from Munnafaisal
+author: John Snow Labs
+name: burmese_awesome_qa_model_munnafaisal
+date: 2024-09-06
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_munnafaisal` is a English model originally trained by Munnafaisal.
+
+{:.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/burmese_awesome_qa_model_munnafaisal_en_5.5.0_3.0_1725652206776.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_munnafaisal_en_5.5.0_3.0_1725652206776.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_munnafaisal","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_munnafaisal", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_munnafaisal|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Munnafaisal/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_qa_model_pechka_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_qa_model_pechka_pipeline_en.md
new file mode 100644
index 00000000000000..2ec46484e26a27
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_qa_model_pechka_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_pechka_pipeline pipeline DistilBertForQuestionAnswering from Pechka
+author: John Snow Labs
+name: burmese_awesome_qa_model_pechka_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_pechka_pipeline` is a English model originally trained by Pechka.
+
+{:.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/burmese_awesome_qa_model_pechka_pipeline_en_5.5.0_3.0_1725622029810.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_pechka_pipeline_en_5.5.0_3.0_1725622029810.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_pechka_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_pechka_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_pechka_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Pechka/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_qa_model_rentao_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_qa_model_rentao_pipeline_en.md
new file mode 100644
index 00000000000000..db2be031b0c5ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_qa_model_rentao_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_rentao_pipeline pipeline DistilBertForQuestionAnswering from Rentao
+author: John Snow Labs
+name: burmese_awesome_qa_model_rentao_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_rentao_pipeline` is a English model originally trained by Rentao.
+
+{:.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/burmese_awesome_qa_model_rentao_pipeline_en_5.5.0_3.0_1725621920563.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_rentao_pipeline_en_5.5.0_3.0_1725621920563.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_rentao_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_rentao_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_rentao_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Rentao/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_wnut_ganeither_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_wnut_ganeither_pipeline_en.md
new file mode 100644
index 00000000000000..cffbfb876bd440
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_wnut_ganeither_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_ganeither_pipeline pipeline DistilBertForTokenClassification from gonzalezrostani
+author: John Snow Labs
+name: burmese_awesome_wnut_ganeither_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_ganeither_pipeline` is a English model originally trained by gonzalezrostani.
+
+{:.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/burmese_awesome_wnut_ganeither_pipeline_en_5.5.0_3.0_1725653941938.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_ganeither_pipeline_en_5.5.0_3.0_1725653941938.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
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_ganeither_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_ganeither_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_ganeither_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/gonzalezrostani/my_awesome_wnut_GAneither
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_wnut_model_adalee1001_en.md b/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_wnut_model_adalee1001_en.md
new file mode 100644
index 00000000000000..9928fac62d6dda
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_wnut_model_adalee1001_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_adalee1001 DistilBertForTokenClassification from Adalee1001
+author: John Snow Labs
+name: burmese_awesome_wnut_model_adalee1001
+date: 2024-09-06
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_adalee1001` is a English model originally trained by Adalee1001.
+
+{:.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/burmese_awesome_wnut_model_adalee1001_en_5.5.0_3.0_1725599586201.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_adalee1001_en_5.5.0_3.0_1725599586201.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_adalee1001","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_adalee1001", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_adalee1001|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Adalee1001/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_wnut_model_megakirito_en.md b/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_wnut_model_megakirito_en.md
new file mode 100644
index 00000000000000..65e34ac04a73a8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_wnut_model_megakirito_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_megakirito DistilBertForTokenClassification from megakirito
+author: John Snow Labs
+name: burmese_awesome_wnut_model_megakirito
+date: 2024-09-06
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_megakirito` is a English model originally trained by megakirito.
+
+{:.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/burmese_awesome_wnut_model_megakirito_en_5.5.0_3.0_1725599097047.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_megakirito_en_5.5.0_3.0_1725599097047.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_megakirito","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_megakirito", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_megakirito|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/megakirito/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_wnut_model_studentmsd1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_wnut_model_studentmsd1_pipeline_en.md
new file mode 100644
index 00000000000000..e07430b74af13b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_wnut_model_studentmsd1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_studentmsd1_pipeline pipeline DistilBertForTokenClassification from studentmsd1
+author: John Snow Labs
+name: burmese_awesome_wnut_model_studentmsd1_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_studentmsd1_pipeline` is a English model originally trained by studentmsd1.
+
+{:.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/burmese_awesome_wnut_model_studentmsd1_pipeline_en_5.5.0_3.0_1725599673278.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_studentmsd1_pipeline_en_5.5.0_3.0_1725599673278.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
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_studentmsd1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_studentmsd1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_studentmsd1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/studentmsd1/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_wnut_model_sweta_14_en.md b/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_wnut_model_sweta_14_en.md
new file mode 100644
index 00000000000000..1cc9b415714c2c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_wnut_model_sweta_14_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_sweta_14 DistilBertForTokenClassification from sweta-14
+author: John Snow Labs
+name: burmese_awesome_wnut_model_sweta_14
+date: 2024-09-06
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_sweta_14` is a English model originally trained by sweta-14.
+
+{:.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/burmese_awesome_wnut_model_sweta_14_en_5.5.0_3.0_1725653485351.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_sweta_14_en_5.5.0_3.0_1725653485351.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_sweta_14","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_sweta_14", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_sweta_14|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/sweta-14/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_wnut_model_sweta_14_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_wnut_model_sweta_14_pipeline_en.md
new file mode 100644
index 00000000000000..c08229b8219231
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-burmese_awesome_wnut_model_sweta_14_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_sweta_14_pipeline pipeline DistilBertForTokenClassification from sweta-14
+author: John Snow Labs
+name: burmese_awesome_wnut_model_sweta_14_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_sweta_14_pipeline` is a English model originally trained by sweta-14.
+
+{:.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/burmese_awesome_wnut_model_sweta_14_pipeline_en_5.5.0_3.0_1725653498204.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_sweta_14_pipeline_en_5.5.0_3.0_1725653498204.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
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_sweta_14_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_sweta_14_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_sweta_14_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/sweta-14/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-burmese_fine_tuning_opus_maltese_english_vietnamese_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-burmese_fine_tuning_opus_maltese_english_vietnamese_model_pipeline_en.md
new file mode 100644
index 00000000000000..0fe17bb6ea213e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-burmese_fine_tuning_opus_maltese_english_vietnamese_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_fine_tuning_opus_maltese_english_vietnamese_model_pipeline pipeline MarianTransformer from Kudod
+author: John Snow Labs
+name: burmese_fine_tuning_opus_maltese_english_vietnamese_model_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_fine_tuning_opus_maltese_english_vietnamese_model_pipeline` is a English model originally trained by Kudod.
+
+{:.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/burmese_fine_tuning_opus_maltese_english_vietnamese_model_pipeline_en_5.5.0_3.0_1725636395929.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_fine_tuning_opus_maltese_english_vietnamese_model_pipeline_en_5.5.0_3.0_1725636395929.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
+
+pipeline = PretrainedPipeline("burmese_fine_tuning_opus_maltese_english_vietnamese_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_fine_tuning_opus_maltese_english_vietnamese_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_fine_tuning_opus_maltese_english_vietnamese_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|475.2 MB|
+
+## References
+
+https://huggingface.co/Kudod/my_fine_tuning_opus_mt_en_vi_model
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-burmese_ner_model_mido545_en.md b/docs/_posts/ahmedlone127/2024-09-06-burmese_ner_model_mido545_en.md
new file mode 100644
index 00000000000000..5e1214dec714f6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-burmese_ner_model_mido545_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_ner_model_mido545 DistilBertForTokenClassification from mido545
+author: John Snow Labs
+name: burmese_ner_model_mido545
+date: 2024-09-06
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_ner_model_mido545` is a English model originally trained by mido545.
+
+{:.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/burmese_ner_model_mido545_en_5.5.0_3.0_1725653657134.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_ner_model_mido545_en_5.5.0_3.0_1725653657134.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_ner_model_mido545","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_ner_model_mido545", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_ner_model_mido545|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/mido545/my_ner_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-burmese_nmt_model_ad_iiitd_en.md b/docs/_posts/ahmedlone127/2024-09-06-burmese_nmt_model_ad_iiitd_en.md
new file mode 100644
index 00000000000000..9467e518c80f08
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-burmese_nmt_model_ad_iiitd_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_nmt_model_ad_iiitd MarianTransformer from AD-IIITD
+author: John Snow Labs
+name: burmese_nmt_model_ad_iiitd
+date: 2024-09-06
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_nmt_model_ad_iiitd` is a English model originally trained by AD-IIITD.
+
+{:.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/burmese_nmt_model_ad_iiitd_en_5.5.0_3.0_1725635345943.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_nmt_model_ad_iiitd_en_5.5.0_3.0_1725635345943.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("burmese_nmt_model_ad_iiitd","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("burmese_nmt_model_ad_iiitd","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_nmt_model_ad_iiitd|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|500.0 MB|
+
+## References
+
+https://huggingface.co/AD-IIITD/my_NMT_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-candle_cvss_interaction_en.md b/docs/_posts/ahmedlone127/2024-09-06-candle_cvss_interaction_en.md
new file mode 100644
index 00000000000000..4812fae7cdb80f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-candle_cvss_interaction_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English candle_cvss_interaction MPNetForSequenceClassification from iashour
+author: John Snow Labs
+name: candle_cvss_interaction
+date: 2024-09-06
+tags: [en, open_source, onnx, sequence_classification, mpnet]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`candle_cvss_interaction` is a English model originally trained by iashour.
+
+{:.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/candle_cvss_interaction_en_5.5.0_3.0_1725655386854.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/candle_cvss_interaction_en_5.5.0_3.0_1725655386854.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = MPNetForSequenceClassification.pretrained("candle_cvss_interaction","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = MPNetForSequenceClassification.pretrained("candle_cvss_interaction", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|candle_cvss_interaction|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.5 MB|
+
+## References
+
+https://huggingface.co/iashour/CANDLE_cvss_interaction
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-clinicalbert_finetune_trial_en.md b/docs/_posts/ahmedlone127/2024-09-06-clinicalbert_finetune_trial_en.md
new file mode 100644
index 00000000000000..93c1ed408ee08b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-clinicalbert_finetune_trial_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English clinicalbert_finetune_trial DistilBertEmbeddings from Peter99
+author: John Snow Labs
+name: clinicalbert_finetune_trial
+date: 2024-09-06
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clinicalbert_finetune_trial` is a English model originally trained by Peter99.
+
+{:.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/clinicalbert_finetune_trial_en_5.5.0_3.0_1725639151060.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clinicalbert_finetune_trial_en_5.5.0_3.0_1725639151060.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("clinicalbert_finetune_trial","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("clinicalbert_finetune_trial","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clinicalbert_finetune_trial|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|505.3 MB|
+
+## References
+
+https://huggingface.co/Peter99/clinicalbert_finetune_trial
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-clinicalbert_finetune_trial_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-clinicalbert_finetune_trial_pipeline_en.md
new file mode 100644
index 00000000000000..07d83d6e211eed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-clinicalbert_finetune_trial_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English clinicalbert_finetune_trial_pipeline pipeline DistilBertEmbeddings from Peter99
+author: John Snow Labs
+name: clinicalbert_finetune_trial_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clinicalbert_finetune_trial_pipeline` is a English model originally trained by Peter99.
+
+{:.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/clinicalbert_finetune_trial_pipeline_en_5.5.0_3.0_1725639177260.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clinicalbert_finetune_trial_pipeline_en_5.5.0_3.0_1725639177260.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
+
+pipeline = PretrainedPipeline("clinicalbert_finetune_trial_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clinicalbert_finetune_trial_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clinicalbert_finetune_trial_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|505.3 MB|
+
+## References
+
+https://huggingface.co/Peter99/clinicalbert_finetune_trial
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-clip_gagan3012_en.md b/docs/_posts/ahmedlone127/2024-09-06-clip_gagan3012_en.md
new file mode 100644
index 00000000000000..e5f9e2faabf9d2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-clip_gagan3012_en.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: English clip_gagan3012 CLIPForZeroShotClassification from gagan3012
+author: John Snow Labs
+name: clip_gagan3012
+date: 2024-09-06
+tags: [en, open_source, onnx, zero_shot, clip, image]
+task: Zero-Shot Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CLIPForZeroShotClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clip_gagan3012` is a English model originally trained by gagan3012.
+
+{:.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/clip_gagan3012_en_5.5.0_3.0_1725650042842.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clip_gagan3012_en_5.5.0_3.0_1725650042842.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
+
+imageDF = spark.read \
+    .format("image") \
+    .option("dropInvalid", value = True) \
+    .load("src/test/resources/image/")
+    
+candidateLabels = [
+    "a photo of a bird",
+    "a photo of a cat",
+    "a photo of a dog",
+    "a photo of a hen",
+    "a photo of a hippo",
+    "a photo of a room",
+    "a photo of a tractor",
+    "a photo of an ostrich",
+    "a photo of an ox"]
+
+ImageAssembler = ImageAssembler() \
+	.setInputCol("image") \
+	.setOutputCol("image_assembler")
+
+imageClassifier = CLIPForZeroShotClassification.pretrained("clip_gagan3012","en") \
+     .setInputCols(["image_assembler"]) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+
+pipeline = Pipeline().setStages([ImageAssembler, imageClassifier])
+pipelineModel = pipeline.fit(imageDF)
+pipelineDF = pipelineModel.transform(imageDF)
+
+
+```
+```scala
+
+		
+val imageDF = ResourceHelper.spark.read
+  .format("image")
+  .option("dropInvalid", value = true)
+  .load("src/test/resources/image/")
+
+val candidateLabels = Array(
+  "a photo of a bird",
+  "a photo of a cat",
+  "a photo of a dog",
+  "a photo of a hen",
+  "a photo of a hippo",
+  "a photo of a room",
+  "a photo of a tractor",
+  "a photo of an ostrich",
+  "a photo of an ox")
+
+val imageAssembler = new ImageAssembler()
+  .setInputCol("image")
+  .setOutputCol("image_assembler")
+  
+val imageClassifier = CLIPForZeroShotClassification.pretrained("clip_gagan3012","en") \
+     .setInputCols(Array("image_assembler")) \
+     .setOutputCol("label") \
+     .setCandidateLabels(candidateLabels)
+  
+val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier))
+val pipelineModel = pipeline.fit(imageDF)
+val pipelineDF = pipelineModel.transform(imageDF)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clip_gagan3012|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[image_assembler]|
+|Output Labels:|[label]|
+|Language:|en|
+|Size:|397.5 MB|
+
+## References
+
+https://huggingface.co/gagan3012/clip
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-deberta_v3_base_rocstories_test_en.md b/docs/_posts/ahmedlone127/2024-09-06-deberta_v3_base_rocstories_test_en.md
new file mode 100644
index 00000000000000..4ccbb2a6d1aadc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-deberta_v3_base_rocstories_test_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_base_rocstories_test DeBertaForSequenceClassification from KeiHeityuu
+author: John Snow Labs
+name: deberta_v3_base_rocstories_test
+date: 2024-09-06
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_rocstories_test` is a English model originally trained by KeiHeityuu.
+
+{:.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/deberta_v3_base_rocstories_test_en_5.5.0_3.0_1725591007496.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_rocstories_test_en_5.5.0_3.0_1725591007496.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_base_rocstories_test","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_rocstories_test", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_rocstories_test|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|575.1 MB|
+
+## References
+
+https://huggingface.co/KeiHeityuu/deberta-v3-base-rocstories-test
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-deberta_v3_bass_complex_questions_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-deberta_v3_bass_complex_questions_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..8d376805c7bcac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-deberta_v3_bass_complex_questions_classifier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_bass_complex_questions_classifier_pipeline pipeline DeBertaForSequenceClassification from nogae
+author: John Snow Labs
+name: deberta_v3_bass_complex_questions_classifier_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_bass_complex_questions_classifier_pipeline` is a English model originally trained by nogae.
+
+{:.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/deberta_v3_bass_complex_questions_classifier_pipeline_en_5.5.0_3.0_1725609971252.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_bass_complex_questions_classifier_pipeline_en_5.5.0_3.0_1725609971252.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
+
+pipeline = PretrainedPipeline("deberta_v3_bass_complex_questions_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_bass_complex_questions_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_bass_complex_questions_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|688.9 MB|
+
+## References
+
+https://huggingface.co/nogae/deberta-v3-bass-complex-questions_classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_gpt4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_gpt4_pipeline_en.md
new file mode 100644
index 00000000000000..eb88406e5a75b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_gpt4_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_gpt4_pipeline pipeline DeBertaForSequenceClassification from domenicrosati
+author: John Snow Labs
+name: deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_gpt4_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_gpt4_pipeline` is a English model originally trained by domenicrosati.
+
+{:.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/deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_gpt4_pipeline_en_5.5.0_3.0_1725610802210.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_gpt4_pipeline_en_5.5.0_3.0_1725610802210.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
+
+pipeline = PretrainedPipeline("deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_gpt4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_gpt4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_survey_nepal_bhasa_fact_related_passage_rater_gpt4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/domenicrosati/deberta-v3-large-survey-new_fact_related_passage-rater-gpt4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-deberta_xsmall_hatespeech_reward_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-deberta_xsmall_hatespeech_reward_model_pipeline_en.md
new file mode 100644
index 00000000000000..f75887282e83ad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-deberta_xsmall_hatespeech_reward_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_xsmall_hatespeech_reward_model_pipeline pipeline DeBertaForSequenceClassification from shahrukhx01
+author: John Snow Labs
+name: deberta_xsmall_hatespeech_reward_model_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_xsmall_hatespeech_reward_model_pipeline` is a English model originally trained by shahrukhx01.
+
+{:.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/deberta_xsmall_hatespeech_reward_model_pipeline_en_5.5.0_3.0_1725609754630.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_xsmall_hatespeech_reward_model_pipeline_en_5.5.0_3.0_1725609754630.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
+
+pipeline = PretrainedPipeline("deberta_xsmall_hatespeech_reward_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_xsmall_hatespeech_reward_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_xsmall_hatespeech_reward_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|253.5 MB|
+
+## References
+
+https://huggingface.co/shahrukhx01/deberta-xsmall-hatespeech-reward-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_cased_finetuned_bible_accelerate_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_cased_finetuned_bible_accelerate_pipeline_en.md
new file mode 100644
index 00000000000000..226c809728051c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_cased_finetuned_bible_accelerate_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_cased_finetuned_bible_accelerate_pipeline pipeline DistilBertEmbeddings from Pragash-Mohanarajah
+author: John Snow Labs
+name: distilbert_base_cased_finetuned_bible_accelerate_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_cased_finetuned_bible_accelerate_pipeline` is a English model originally trained by Pragash-Mohanarajah.
+
+{:.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/distilbert_base_cased_finetuned_bible_accelerate_pipeline_en_5.5.0_3.0_1725639173224.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_cased_finetuned_bible_accelerate_pipeline_en_5.5.0_3.0_1725639173224.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
+
+pipeline = PretrainedPipeline("distilbert_base_cased_finetuned_bible_accelerate_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_cased_finetuned_bible_accelerate_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_cased_finetuned_bible_accelerate_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.7 MB|
+
+## References
+
+https://huggingface.co/Pragash-Mohanarajah/distilbert-base-cased-finetuned-bible-accelerate
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_finetuned_imdb_gnider_en.md b/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_finetuned_imdb_gnider_en.md
new file mode 100644
index 00000000000000..a0cf5acf3a0aa9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_finetuned_imdb_gnider_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_gnider DistilBertEmbeddings from Gnider
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_gnider
+date: 2024-09-06
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_gnider` is a English model originally trained by Gnider.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_gnider_en_5.5.0_3.0_1725664954450.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_gnider_en_5.5.0_3.0_1725664954450.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_gnider","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_gnider","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_gnider|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Gnider/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_finetuned_imdb_hf_tutorial_using_accelerate_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_finetuned_imdb_hf_tutorial_using_accelerate_pipeline_en.md
new file mode 100644
index 00000000000000..896bdc0f719441
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_finetuned_imdb_hf_tutorial_using_accelerate_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_hf_tutorial_using_accelerate_pipeline pipeline DistilBertEmbeddings from thuann2cats
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_hf_tutorial_using_accelerate_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_hf_tutorial_using_accelerate_pipeline` is a English model originally trained by thuann2cats.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_hf_tutorial_using_accelerate_pipeline_en_5.5.0_3.0_1725664839708.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_hf_tutorial_using_accelerate_pipeline_en_5.5.0_3.0_1725664839708.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_hf_tutorial_using_accelerate_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_hf_tutorial_using_accelerate_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_hf_tutorial_using_accelerate_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/thuann2cats/distilbert-base-uncased-finetuned-imdb-HF-tutorial-using-accelerate
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_finetuned_imdb_nourhanabosaeed_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_finetuned_imdb_nourhanabosaeed_pipeline_en.md
new file mode 100644
index 00000000000000..765b4763db7658
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_finetuned_imdb_nourhanabosaeed_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_nourhanabosaeed_pipeline pipeline DistilBertEmbeddings from NourhanAbosaeed
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_nourhanabosaeed_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_nourhanabosaeed_pipeline` is a English model originally trained by NourhanAbosaeed.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_nourhanabosaeed_pipeline_en_5.5.0_3.0_1725664783519.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_nourhanabosaeed_pipeline_en_5.5.0_3.0_1725664783519.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_nourhanabosaeed_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_nourhanabosaeed_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_nourhanabosaeed_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/NourhanAbosaeed/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_finetuned_res_ds_accelerate_en.md b/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_finetuned_res_ds_accelerate_en.md
new file mode 100644
index 00000000000000..3b8dd0bfdd2479
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_finetuned_res_ds_accelerate_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_res_ds_accelerate DistilBertEmbeddings from rohbro
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_res_ds_accelerate
+date: 2024-09-06
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_res_ds_accelerate` is a English model originally trained by rohbro.
+
+{:.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/distilbert_base_uncased_finetuned_res_ds_accelerate_en_5.5.0_3.0_1725665126780.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_res_ds_accelerate_en_5.5.0_3.0_1725665126780.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_res_ds_accelerate","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_res_ds_accelerate","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_res_ds_accelerate|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/rohbro/distilbert-base-uncased-finetuned-res_ds-accelerate
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_finetuned_res_ds_accelerate_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_finetuned_res_ds_accelerate_pipeline_en.md
new file mode 100644
index 00000000000000..3759f9294f05ae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_finetuned_res_ds_accelerate_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_res_ds_accelerate_pipeline pipeline DistilBertEmbeddings from rohbro
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_res_ds_accelerate_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_res_ds_accelerate_pipeline` is a English model originally trained by rohbro.
+
+{:.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/distilbert_base_uncased_finetuned_res_ds_accelerate_pipeline_en_5.5.0_3.0_1725665138804.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_res_ds_accelerate_pipeline_en_5.5.0_3.0_1725665138804.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_res_ds_accelerate_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_res_ds_accelerate_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_res_ds_accelerate_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/rohbro/distilbert-base-uncased-finetuned-res_ds-accelerate
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_finetuned_squad_blaze07_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_finetuned_squad_blaze07_pipeline_en.md
new file mode 100644
index 00000000000000..de1d34f49cdf26
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_finetuned_squad_blaze07_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_blaze07_pipeline pipeline DistilBertForQuestionAnswering from Blaze07
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_blaze07_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_blaze07_pipeline` is a English model originally trained by Blaze07.
+
+{:.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/distilbert_base_uncased_finetuned_squad_blaze07_pipeline_en_5.5.0_3.0_1725652239028.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_blaze07_pipeline_en_5.5.0_3.0_1725652239028.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_blaze07_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_blaze07_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_blaze07_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Blaze07/distilbert-base-uncased-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_finetuned_squad_csmuaic_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_finetuned_squad_csmuaic_pipeline_en.md
new file mode 100644
index 00000000000000..671afd2e646bce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_finetuned_squad_csmuaic_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_csmuaic_pipeline pipeline DistilBertForQuestionAnswering from csmuaic
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_csmuaic_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_csmuaic_pipeline` is a English model originally trained by csmuaic.
+
+{:.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/distilbert_base_uncased_finetuned_squad_csmuaic_pipeline_en_5.5.0_3.0_1725621944456.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_csmuaic_pipeline_en_5.5.0_3.0_1725621944456.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_csmuaic_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_csmuaic_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_csmuaic_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/csmuaic/distilbert-base-uncased-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_finetuned_squad_d5716d28_soduhh_en.md b/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_finetuned_squad_d5716d28_soduhh_en.md
new file mode 100644
index 00000000000000..6ebe49a74d2b9e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_finetuned_squad_d5716d28_soduhh_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_d5716d28_soduhh DistilBertEmbeddings from soduhh
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_d5716d28_soduhh
+date: 2024-09-06
+tags: [distilbert, en, open_source, fill_mask, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings  model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_d5716d28_soduhh` is a English model originally trained by soduhh.
+
+## 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/distilbert_base_uncased_finetuned_squad_d5716d28_soduhh_en_5.5.0_3.0_1725652647564.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_d5716d28_soduhh_en_5.5.0_3.0_1725652647564.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 =DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_squad_d5716d28_soduhh","en") \
+            .setInputCols(["documents","token"]) \
+            .setOutputCol("embeddings")
+
+pipeline = Pipeline().setStages([document_assembler, embeddings])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("embeddings")
+    
+val embeddings = DistilBertEmbeddings 
+    .pretrained("distilbert_base_uncased_finetuned_squad_d5716d28_soduhh", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("embeddings") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_d5716d28_soduhh|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+References
+
+https://huggingface.co/soduhh/distilbert-base-uncased-finetuned-squad-d5716d28
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_finetuned_squad_d5716d28_soduhh_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_finetuned_squad_d5716d28_soduhh_pipeline_en.md
new file mode 100644
index 00000000000000..c9f843b813cad5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_finetuned_squad_d5716d28_soduhh_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_d5716d28_soduhh_pipeline pipeline DistilBertForQuestionAnswering from soduhh
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_d5716d28_soduhh_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_d5716d28_soduhh_pipeline` is a English model originally trained by soduhh.
+
+{:.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/distilbert_base_uncased_finetuned_squad_d5716d28_soduhh_pipeline_en_5.5.0_3.0_1725652661813.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_d5716d28_soduhh_pipeline_en_5.5.0_3.0_1725652661813.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_d5716d28_soduhh_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_d5716d28_soduhh_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_d5716d28_soduhh_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/soduhh/distilbert-base-uncased-finetuned-squad-d5716d28
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_finetuned_squad_inseokteo_en.md b/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_finetuned_squad_inseokteo_en.md
new file mode 100644
index 00000000000000..35cfc8aec99412
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_finetuned_squad_inseokteo_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_inseokteo DistilBertForQuestionAnswering from inseokteo
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_inseokteo
+date: 2024-09-06
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_inseokteo` is a English model originally trained by inseokteo.
+
+{:.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/distilbert_base_uncased_finetuned_squad_inseokteo_en_5.5.0_3.0_1725621929477.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_inseokteo_en_5.5.0_3.0_1725621929477.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_inseokteo","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_inseokteo", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_inseokteo|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/inseokteo/distilbert-base-uncased-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_ner_pipeline_en.md
new file mode 100644
index 00000000000000..a17e8841e0e784
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_ner_pipeline pipeline DistilBertForTokenClassification from douglasadams11
+author: John Snow Labs
+name: distilbert_base_uncased_ner_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_ner_pipeline` is a English model originally trained by douglasadams11.
+
+{:.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/distilbert_base_uncased_ner_pipeline_en_5.5.0_3.0_1725599561392.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_ner_pipeline_en_5.5.0_3.0_1725599561392.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/douglasadams11/distilbert-base-uncased-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_question_answering_en.md b/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_question_answering_en.md
new file mode 100644
index 00000000000000..ec2d9e3b69d11a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-distilbert_base_uncased_question_answering_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_base_uncased_question_answering DistilBertForQuestionAnswering from farzanrahmani
+author: John Snow Labs
+name: distilbert_base_uncased_question_answering
+date: 2024-09-06
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_question_answering` is a English model originally trained by farzanrahmani.
+
+{:.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/distilbert_base_uncased_question_answering_en_5.5.0_3.0_1725654778402.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_question_answering_en_5.5.0_3.0_1725654778402.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_question_answering","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_question_answering", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_question_answering|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/farzanrahmani/distilbert_base_uncased_question_answering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-distilbert_extractive_qa_project_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-distilbert_extractive_qa_project_pipeline_en.md
new file mode 100644
index 00000000000000..e44d917d87199e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-distilbert_extractive_qa_project_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_extractive_qa_project_pipeline pipeline DistilBertForQuestionAnswering from amara16
+author: John Snow Labs
+name: distilbert_extractive_qa_project_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_extractive_qa_project_pipeline` is a English model originally trained by amara16.
+
+{:.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/distilbert_extractive_qa_project_pipeline_en_5.5.0_3.0_1725652754301.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_extractive_qa_project_pipeline_en_5.5.0_3.0_1725652754301.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
+
+pipeline = PretrainedPipeline("distilbert_extractive_qa_project_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_extractive_qa_project_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_extractive_qa_project_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/amara16/distilbert-extractive-qa-project
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-distilbert_finetuned_squad_droo303_en.md b/docs/_posts/ahmedlone127/2024-09-06-distilbert_finetuned_squad_droo303_en.md
new file mode 100644
index 00000000000000..1484b1a04c0eae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-distilbert_finetuned_squad_droo303_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_finetuned_squad_droo303 DistilBertForQuestionAnswering from droo303
+author: John Snow Labs
+name: distilbert_finetuned_squad_droo303
+date: 2024-09-06
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_squad_droo303` is a English model originally trained by droo303.
+
+{:.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/distilbert_finetuned_squad_droo303_en_5.5.0_3.0_1725655016278.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_squad_droo303_en_5.5.0_3.0_1725655016278.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_finetuned_squad_droo303","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_finetuned_squad_droo303", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_squad_droo303|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/droo303/distilbert-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-distilbert_heaps_masked_en.md b/docs/_posts/ahmedlone127/2024-09-06-distilbert_heaps_masked_en.md
new file mode 100644
index 00000000000000..3c90d7c7e22f4e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-distilbert_heaps_masked_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_heaps_masked DistilBertEmbeddings from johannes-garstenauer
+author: John Snow Labs
+name: distilbert_heaps_masked
+date: 2024-09-06
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_heaps_masked` is a English model originally trained by johannes-garstenauer.
+
+{:.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/distilbert_heaps_masked_en_5.5.0_3.0_1725664639455.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_heaps_masked_en_5.5.0_3.0_1725664639455.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_heaps_masked","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_heaps_masked","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_heaps_masked|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|248.0 MB|
+
+## References
+
+https://huggingface.co/johannes-garstenauer/distilbert-heaps-masked
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-distilbert_heaps_masked_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-distilbert_heaps_masked_pipeline_en.md
new file mode 100644
index 00000000000000..197d6ce6dbd119
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-distilbert_heaps_masked_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_heaps_masked_pipeline pipeline DistilBertEmbeddings from johannes-garstenauer
+author: John Snow Labs
+name: distilbert_heaps_masked_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_heaps_masked_pipeline` is a English model originally trained by johannes-garstenauer.
+
+{:.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/distilbert_heaps_masked_pipeline_en_5.5.0_3.0_1725664651363.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_heaps_masked_pipeline_en_5.5.0_3.0_1725664651363.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
+
+pipeline = PretrainedPipeline("distilbert_heaps_masked_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_heaps_masked_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_heaps_masked_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|248.0 MB|
+
+## References
+
+https://huggingface.co/johannes-garstenauer/distilbert-heaps-masked
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-distilbert_qa_english_german_spanish_model_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-06-distilbert_qa_english_german_spanish_model_pipeline_xx.md
new file mode 100644
index 00000000000000..74a034dcba0e72
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-distilbert_qa_english_german_spanish_model_pipeline_xx.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Multilingual distilbert_qa_english_german_spanish_model_pipeline pipeline DistilBertForQuestionAnswering from ZYW
+author: John Snow Labs
+name: distilbert_qa_english_german_spanish_model_pipeline
+date: 2024-09-06
+tags: [xx, open_source, pipeline, onnx]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_qa_english_german_spanish_model_pipeline` is a Multilingual model originally trained by ZYW.
+
+{:.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/distilbert_qa_english_german_spanish_model_pipeline_xx_5.5.0_3.0_1725622181992.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_qa_english_german_spanish_model_pipeline_xx_5.5.0_3.0_1725622181992.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
+
+pipeline = PretrainedPipeline("distilbert_qa_english_german_spanish_model_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_qa_english_german_spanish_model_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_qa_english_german_spanish_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/ZYW/en-de-es-model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-distillbert_newscategoryclassification_fullmodel_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-distillbert_newscategoryclassification_fullmodel_3_pipeline_en.md
new file mode 100644
index 00000000000000..ec3be1124e718b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-distillbert_newscategoryclassification_fullmodel_3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distillbert_newscategoryclassification_fullmodel_3_pipeline pipeline DistilBertForSequenceClassification from akashmaggon
+author: John Snow Labs
+name: distillbert_newscategoryclassification_fullmodel_3_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distillbert_newscategoryclassification_fullmodel_3_pipeline` is a English model originally trained by akashmaggon.
+
+{:.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/distillbert_newscategoryclassification_fullmodel_3_pipeline_en_5.5.0_3.0_1725608351455.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distillbert_newscategoryclassification_fullmodel_3_pipeline_en_5.5.0_3.0_1725608351455.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
+
+pipeline = PretrainedPipeline("distillbert_newscategoryclassification_fullmodel_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distillbert_newscategoryclassification_fullmodel_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distillbert_newscategoryclassification_fullmodel_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|250.4 MB|
+
+## References
+
+https://huggingface.co/akashmaggon/distillbert-newscategoryclassification-fullmodel-3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-dummy_model_ericchchiu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-dummy_model_ericchchiu_pipeline_en.md
new file mode 100644
index 00000000000000..f1b1da1de18e29
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-dummy_model_ericchchiu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_ericchchiu_pipeline pipeline CamemBertEmbeddings from ericchchiu
+author: John Snow Labs
+name: dummy_model_ericchchiu_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_ericchchiu_pipeline` is a English model originally trained by ericchchiu.
+
+{:.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/dummy_model_ericchchiu_pipeline_en_5.5.0_3.0_1725632905862.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_ericchchiu_pipeline_en_5.5.0_3.0_1725632905862.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
+
+pipeline = PretrainedPipeline("dummy_model_ericchchiu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_ericchchiu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_ericchchiu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/ericchchiu/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-dummy_model_exilesaber_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-dummy_model_exilesaber_pipeline_en.md
new file mode 100644
index 00000000000000..e6bee82dc54b0f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-dummy_model_exilesaber_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_exilesaber_pipeline pipeline CamemBertEmbeddings from ExileSaber
+author: John Snow Labs
+name: dummy_model_exilesaber_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_exilesaber_pipeline` is a English model originally trained by ExileSaber.
+
+{:.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/dummy_model_exilesaber_pipeline_en_5.5.0_3.0_1725632514703.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_exilesaber_pipeline_en_5.5.0_3.0_1725632514703.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
+
+pipeline = PretrainedPipeline("dummy_model_exilesaber_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_exilesaber_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_exilesaber_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/ExileSaber/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-dummy_model_jp1773hsu_en.md b/docs/_posts/ahmedlone127/2024-09-06-dummy_model_jp1773hsu_en.md
new file mode 100644
index 00000000000000..542448c1cf6795
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-dummy_model_jp1773hsu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_jp1773hsu CamemBertEmbeddings from jp1773hsu
+author: John Snow Labs
+name: dummy_model_jp1773hsu
+date: 2024-09-06
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jp1773hsu` is a English model originally trained by jp1773hsu.
+
+{:.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/dummy_model_jp1773hsu_en_5.5.0_3.0_1725631859993.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jp1773hsu_en_5.5.0_3.0_1725631859993.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_jp1773hsu","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_jp1773hsu","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_jp1773hsu|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/jp1773hsu/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-dummy_model_lourvalli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-dummy_model_lourvalli_pipeline_en.md
new file mode 100644
index 00000000000000..b01737417bc799
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-dummy_model_lourvalli_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_lourvalli_pipeline pipeline CamemBertEmbeddings from lourvalli
+author: John Snow Labs
+name: dummy_model_lourvalli_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_lourvalli_pipeline` is a English model originally trained by lourvalli.
+
+{:.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/dummy_model_lourvalli_pipeline_en_5.5.0_3.0_1725637188924.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_lourvalli_pipeline_en_5.5.0_3.0_1725637188924.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
+
+pipeline = PretrainedPipeline("dummy_model_lourvalli_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_lourvalli_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_lourvalli_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/lourvalli/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-dummy_model_rizwanakt_en.md b/docs/_posts/ahmedlone127/2024-09-06-dummy_model_rizwanakt_en.md
new file mode 100644
index 00000000000000..cb38e8ffc3fcbf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-dummy_model_rizwanakt_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_rizwanakt CamemBertEmbeddings from Rizwanakt
+author: John Snow Labs
+name: dummy_model_rizwanakt
+date: 2024-09-06
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_rizwanakt` is a English model originally trained by Rizwanakt.
+
+{:.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/dummy_model_rizwanakt_en_5.5.0_3.0_1725632736713.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_rizwanakt_en_5.5.0_3.0_1725632736713.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_rizwanakt","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_rizwanakt","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_rizwanakt|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Rizwanakt/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-dummy_model_sapphirejade_en.md b/docs/_posts/ahmedlone127/2024-09-06-dummy_model_sapphirejade_en.md
new file mode 100644
index 00000000000000..a73d204c36c5aa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-dummy_model_sapphirejade_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_sapphirejade CamemBertEmbeddings from sapphirejade
+author: John Snow Labs
+name: dummy_model_sapphirejade
+date: 2024-09-06
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_sapphirejade` is a English model originally trained by sapphirejade.
+
+{:.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/dummy_model_sapphirejade_en_5.5.0_3.0_1725632253838.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_sapphirejade_en_5.5.0_3.0_1725632253838.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_sapphirejade","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_sapphirejade","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_sapphirejade|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/sapphirejade/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-dummy_model_srushnaik_en.md b/docs/_posts/ahmedlone127/2024-09-06-dummy_model_srushnaik_en.md
new file mode 100644
index 00000000000000..1cd5949221b32b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-dummy_model_srushnaik_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_srushnaik CamemBertEmbeddings from SrushNaik
+author: John Snow Labs
+name: dummy_model_srushnaik
+date: 2024-09-06
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_srushnaik` is a English model originally trained by SrushNaik.
+
+{:.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/dummy_model_srushnaik_en_5.5.0_3.0_1725631887279.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_srushnaik_en_5.5.0_3.0_1725631887279.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_srushnaik","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_srushnaik","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_srushnaik|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/SrushNaik/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-english_coptic_norm_group_greekified_bt_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-english_coptic_norm_group_greekified_bt_pipeline_en.md
new file mode 100644
index 00000000000000..de774c369dca86
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-english_coptic_norm_group_greekified_bt_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English english_coptic_norm_group_greekified_bt_pipeline pipeline MarianTransformer from megalaa
+author: John Snow Labs
+name: english_coptic_norm_group_greekified_bt_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_coptic_norm_group_greekified_bt_pipeline` is a English model originally trained by megalaa.
+
+{:.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/english_coptic_norm_group_greekified_bt_pipeline_en_5.5.0_3.0_1725635381268.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_coptic_norm_group_greekified_bt_pipeline_en_5.5.0_3.0_1725635381268.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
+
+pipeline = PretrainedPipeline("english_coptic_norm_group_greekified_bt_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("english_coptic_norm_group_greekified_bt_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_coptic_norm_group_greekified_bt_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|530.8 MB|
+
+## References
+
+https://huggingface.co/megalaa/en-cop-norm-group-greekified-bt
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-extract_question_from_text_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-extract_question_from_text_pipeline_en.md
new file mode 100644
index 00000000000000..86025f633941cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-extract_question_from_text_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English extract_question_from_text_pipeline pipeline DistilBertForQuestionAnswering from wdavies
+author: John Snow Labs
+name: extract_question_from_text_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`extract_question_from_text_pipeline` is a English model originally trained by wdavies.
+
+{:.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/extract_question_from_text_pipeline_en_5.5.0_3.0_1725652789098.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/extract_question_from_text_pipeline_en_5.5.0_3.0_1725652789098.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
+
+pipeline = PretrainedPipeline("extract_question_from_text_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("extract_question_from_text_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|extract_question_from_text_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/wdavies/extract-question-from-text
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-few_shot_learner_en.md b/docs/_posts/ahmedlone127/2024-09-06-few_shot_learner_en.md
new file mode 100644
index 00000000000000..daeba23bc8b65e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-few_shot_learner_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English few_shot_learner MPNetEmbeddings from ManuelaJeyaraj
+author: John Snow Labs
+name: few_shot_learner
+date: 2024-09-06
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`few_shot_learner` is a English model originally trained by ManuelaJeyaraj.
+
+{:.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/few_shot_learner_en_5.5.0_3.0_1725595462325.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/few_shot_learner_en_5.5.0_3.0_1725595462325.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("few_shot_learner","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("few_shot_learner","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|few_shot_learner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/ManuelaJeyaraj/few_shot_learner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-finetuned_helsinki_nlp_english_marathi_marh_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-finetuned_helsinki_nlp_english_marathi_marh_pipeline_en.md
new file mode 100644
index 00000000000000..2ca9b68b0b8b1d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-finetuned_helsinki_nlp_english_marathi_marh_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuned_helsinki_nlp_english_marathi_marh_pipeline pipeline MarianTransformer from anujsahani01
+author: John Snow Labs
+name: finetuned_helsinki_nlp_english_marathi_marh_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_helsinki_nlp_english_marathi_marh_pipeline` is a English model originally trained by anujsahani01.
+
+{:.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/finetuned_helsinki_nlp_english_marathi_marh_pipeline_en_5.5.0_3.0_1725636143526.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_helsinki_nlp_english_marathi_marh_pipeline_en_5.5.0_3.0_1725636143526.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
+
+pipeline = PretrainedPipeline("finetuned_helsinki_nlp_english_marathi_marh_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_helsinki_nlp_english_marathi_marh_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_helsinki_nlp_english_marathi_marh_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|520.6 MB|
+
+## References
+
+https://huggingface.co/anujsahani01/finetuned_Helsinki-NLP-en-mr
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-finetuned_opusmt_english_hindi_gujarati_en.md b/docs/_posts/ahmedlone127/2024-09-06-finetuned_opusmt_english_hindi_gujarati_en.md
new file mode 100644
index 00000000000000..b2041c0c64155d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-finetuned_opusmt_english_hindi_gujarati_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuned_opusmt_english_hindi_gujarati MarianTransformer from Varsha00
+author: John Snow Labs
+name: finetuned_opusmt_english_hindi_gujarati
+date: 2024-09-06
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_opusmt_english_hindi_gujarati` is a English model originally trained by Varsha00.
+
+{:.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/finetuned_opusmt_english_hindi_gujarati_en_5.5.0_3.0_1725636328890.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_opusmt_english_hindi_gujarati_en_5.5.0_3.0_1725636328890.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("finetuned_opusmt_english_hindi_gujarati","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("finetuned_opusmt_english_hindi_gujarati","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_opusmt_english_hindi_gujarati|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|530.1 MB|
+
+## References
+
+https://huggingface.co/Varsha00/finetuned-opusmt-en-hi-gu
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-gbert_base_de.md b/docs/_posts/ahmedlone127/2024-09-06-gbert_base_de.md
new file mode 100644
index 00000000000000..2ba6934683a36f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-gbert_base_de.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: German gbert_base BertEmbeddings from deepset
+author: John Snow Labs
+name: gbert_base
+date: 2024-09-06
+tags: [de, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gbert_base` is a German model originally trained by deepset.
+
+{:.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/gbert_base_de_5.5.0_3.0_1725614924113.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gbert_base_de_5.5.0_3.0_1725614924113.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("gbert_base","de") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("gbert_base","de") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gbert_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|de|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/deepset/gbert-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-gbert_base_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-06-gbert_base_pipeline_de.md
new file mode 100644
index 00000000000000..64d96b90016439
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-gbert_base_pipeline_de.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: German gbert_base_pipeline pipeline BertEmbeddings from deepset
+author: John Snow Labs
+name: gbert_base_pipeline
+date: 2024-09-06
+tags: [de, open_source, pipeline, onnx]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gbert_base_pipeline` is a German model originally trained by deepset.
+
+{:.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/gbert_base_pipeline_de_5.5.0_3.0_1725614944238.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gbert_base_pipeline_de_5.5.0_3.0_1725614944238.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
+
+pipeline = PretrainedPipeline("gbert_base_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gbert_base_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gbert_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|409.8 MB|
+
+## References
+
+https://huggingface.co/deepset/gbert-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-hf_qa_distilbert_base_uncased_en.md b/docs/_posts/ahmedlone127/2024-09-06-hf_qa_distilbert_base_uncased_en.md
new file mode 100644
index 00000000000000..d21b5a78c08eb1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-hf_qa_distilbert_base_uncased_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English hf_qa_distilbert_base_uncased DistilBertForQuestionAnswering from rinogrego
+author: John Snow Labs
+name: hf_qa_distilbert_base_uncased
+date: 2024-09-06
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hf_qa_distilbert_base_uncased` is a English model originally trained by rinogrego.
+
+{:.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/hf_qa_distilbert_base_uncased_en_5.5.0_3.0_1725652745205.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hf_qa_distilbert_base_uncased_en_5.5.0_3.0_1725652745205.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("hf_qa_distilbert_base_uncased","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("hf_qa_distilbert_base_uncased", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hf_qa_distilbert_base_uncased|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/rinogrego/HF-QA-distilbert-base-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-inde_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-inde_1_pipeline_en.md
new file mode 100644
index 00000000000000..aa987405011f74
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-inde_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English inde_1_pipeline pipeline RoBertaForSequenceClassification from BaronSch
+author: John Snow Labs
+name: inde_1_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`inde_1_pipeline` is a English model originally trained by BaronSch.
+
+{:.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/inde_1_pipeline_en_5.5.0_3.0_1725612987745.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/inde_1_pipeline_en_5.5.0_3.0_1725612987745.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
+
+pipeline = PretrainedPipeline("inde_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("inde_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|inde_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.5 MB|
+
+## References
+
+https://huggingface.co/BaronSch/Inde_1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-investopedia_qna_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-investopedia_qna_pipeline_en.md
new file mode 100644
index 00000000000000..9facafe617c571
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-investopedia_qna_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English investopedia_qna_pipeline pipeline DistilBertForQuestionAnswering from ruishan-lin
+author: John Snow Labs
+name: investopedia_qna_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`investopedia_qna_pipeline` is a English model originally trained by ruishan-lin.
+
+{:.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/investopedia_qna_pipeline_en_5.5.0_3.0_1725622106668.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/investopedia_qna_pipeline_en_5.5.0_3.0_1725622106668.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
+
+pipeline = PretrainedPipeline("investopedia_qna_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("investopedia_qna_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|investopedia_qna_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/ruishan-lin/investopedia-QnA
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-marian_finetuned_kde4_chinese_tonga_tonga_islands_english_charliealex123_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-marian_finetuned_kde4_chinese_tonga_tonga_islands_english_charliealex123_pipeline_en.md
new file mode 100644
index 00000000000000..0cbb46dec3c156
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-marian_finetuned_kde4_chinese_tonga_tonga_islands_english_charliealex123_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English marian_finetuned_kde4_chinese_tonga_tonga_islands_english_charliealex123_pipeline pipeline MarianTransformer from charliealex123
+author: John Snow Labs
+name: marian_finetuned_kde4_chinese_tonga_tonga_islands_english_charliealex123_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_chinese_tonga_tonga_islands_english_charliealex123_pipeline` is a English model originally trained by charliealex123.
+
+{:.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/marian_finetuned_kde4_chinese_tonga_tonga_islands_english_charliealex123_pipeline_en_5.5.0_3.0_1725635188186.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_chinese_tonga_tonga_islands_english_charliealex123_pipeline_en_5.5.0_3.0_1725635188186.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
+
+pipeline = PretrainedPipeline("marian_finetuned_kde4_chinese_tonga_tonga_islands_english_charliealex123_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("marian_finetuned_kde4_chinese_tonga_tonga_islands_english_charliealex123_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_chinese_tonga_tonga_islands_english_charliealex123_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|540.6 MB|
+
+## References
+
+https://huggingface.co/charliealex123/marian-finetuned-kde4-zh-to-en
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-marian_finetuned_kde4_english_tonga_tonga_islands_french_phong12azq_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-marian_finetuned_kde4_english_tonga_tonga_islands_french_phong12azq_pipeline_en.md
new file mode 100644
index 00000000000000..ae74b089b25ae8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-marian_finetuned_kde4_english_tonga_tonga_islands_french_phong12azq_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_phong12azq_pipeline pipeline MarianTransformer from phong12azq
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_phong12azq_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_phong12azq_pipeline` is a English model originally trained by phong12azq.
+
+{:.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/marian_finetuned_kde4_english_tonga_tonga_islands_french_phong12azq_pipeline_en_5.5.0_3.0_1725635219384.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_phong12azq_pipeline_en_5.5.0_3.0_1725635219384.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
+
+pipeline = PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_phong12azq_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_phong12azq_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_phong12azq_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|508.6 MB|
+
+## References
+
+https://huggingface.co/phong12azq/marian-finetuned-kde4-en-to-fr
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-mdeberta_v3_base_hatebr_pt.md b/docs/_posts/ahmedlone127/2024-09-06-mdeberta_v3_base_hatebr_pt.md
new file mode 100644
index 00000000000000..160ca786c34203
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-mdeberta_v3_base_hatebr_pt.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Portuguese mdeberta_v3_base_hatebr DeBertaForSequenceClassification from ruanchaves
+author: John Snow Labs
+name: mdeberta_v3_base_hatebr
+date: 2024-09-06
+tags: [pt, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: pt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_hatebr` is a Portuguese model originally trained by ruanchaves.
+
+{:.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/mdeberta_v3_base_hatebr_pt_5.5.0_3.0_1725590858382.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_hatebr_pt_5.5.0_3.0_1725590858382.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_hatebr","pt") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_hatebr", "pt")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_hatebr|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|pt|
+|Size:|844.9 MB|
+
+## References
+
+https://huggingface.co/ruanchaves/mdeberta-v3-base-hatebr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-med_bert_en.md b/docs/_posts/ahmedlone127/2024-09-06-med_bert_en.md
new file mode 100644
index 00000000000000..632a6a654a6549
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-med_bert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English med_bert BertForTokenClassification from praneethvasarla
+author: John Snow Labs
+name: med_bert
+date: 2024-09-06
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`med_bert` is a English model originally trained by praneethvasarla.
+
+{:.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/med_bert_en_5.5.0_3.0_1725634292967.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/med_bert_en_5.5.0_3.0_1725634292967.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("med_bert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("med_bert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|med_bert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/praneethvasarla/med-bert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-mnli_microsoft_deberta_v3_base_seed_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-mnli_microsoft_deberta_v3_base_seed_2_pipeline_en.md
new file mode 100644
index 00000000000000..60dbe9851fd092
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-mnli_microsoft_deberta_v3_base_seed_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mnli_microsoft_deberta_v3_base_seed_2_pipeline pipeline DeBertaForSequenceClassification from utahnlp
+author: John Snow Labs
+name: mnli_microsoft_deberta_v3_base_seed_2_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mnli_microsoft_deberta_v3_base_seed_2_pipeline` is a English model originally trained by utahnlp.
+
+{:.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/mnli_microsoft_deberta_v3_base_seed_2_pipeline_en_5.5.0_3.0_1725589652228.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mnli_microsoft_deberta_v3_base_seed_2_pipeline_en_5.5.0_3.0_1725589652228.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
+
+pipeline = PretrainedPipeline("mnli_microsoft_deberta_v3_base_seed_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mnli_microsoft_deberta_v3_base_seed_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mnli_microsoft_deberta_v3_base_seed_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|641.2 MB|
+
+## References
+
+https://huggingface.co/utahnlp/mnli_microsoft_deberta-v3-base_seed-2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-ner_model_maccrobat_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-ner_model_maccrobat_pipeline_en.md
new file mode 100644
index 00000000000000..6be340aefd417b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-ner_model_maccrobat_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_model_maccrobat_pipeline pipeline DistilBertForTokenClassification from DepressedSage
+author: John Snow Labs
+name: ner_model_maccrobat_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_model_maccrobat_pipeline` is a English model originally trained by DepressedSage.
+
+{:.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/ner_model_maccrobat_pipeline_en_5.5.0_3.0_1725654157929.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_model_maccrobat_pipeline_en_5.5.0_3.0_1725654157929.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
+
+pipeline = PretrainedPipeline("ner_model_maccrobat_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_model_maccrobat_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_model_maccrobat_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.5 MB|
+
+## References
+
+https://huggingface.co/DepressedSage/ner_model_MACCROBAT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-ojobert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-ojobert_pipeline_en.md
new file mode 100644
index 00000000000000..b0f590f64e420b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-ojobert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ojobert_pipeline pipeline DistilBertEmbeddings from ihk
+author: John Snow Labs
+name: ojobert_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ojobert_pipeline` is a English model originally trained by ihk.
+
+{:.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/ojobert_pipeline_en_5.5.0_3.0_1725639650091.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ojobert_pipeline_en_5.5.0_3.0_1725639650091.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
+
+pipeline = PretrainedPipeline("ojobert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ojobert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ojobert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/ihk/ojobert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-ope_bert_v2_1_en.md b/docs/_posts/ahmedlone127/2024-09-06-ope_bert_v2_1_en.md
new file mode 100644
index 00000000000000..9ef16e881ac8ce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-ope_bert_v2_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ope_bert_v2_1 BertEmbeddings from RyotaroOKabe
+author: John Snow Labs
+name: ope_bert_v2_1
+date: 2024-09-06
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ope_bert_v2_1` is a English model originally trained by RyotaroOKabe.
+
+{:.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/ope_bert_v2_1_en_5.5.0_3.0_1725614450711.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ope_bert_v2_1_en_5.5.0_3.0_1725614450711.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("ope_bert_v2_1","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("ope_bert_v2_1","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ope_bert_v2_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/RyotaroOKabe/ope_bert_v2.1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-perspective_conditional_utilitarian_deberta_01_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-perspective_conditional_utilitarian_deberta_01_pipeline_en.md
new file mode 100644
index 00000000000000..eeb7c76fe49613
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-perspective_conditional_utilitarian_deberta_01_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English perspective_conditional_utilitarian_deberta_01_pipeline pipeline DeBertaForSequenceClassification from edmundmills
+author: John Snow Labs
+name: perspective_conditional_utilitarian_deberta_01_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`perspective_conditional_utilitarian_deberta_01_pipeline` is a English model originally trained by edmundmills.
+
+{:.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/perspective_conditional_utilitarian_deberta_01_pipeline_en_5.5.0_3.0_1725611703221.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/perspective_conditional_utilitarian_deberta_01_pipeline_en_5.5.0_3.0_1725611703221.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
+
+pipeline = PretrainedPipeline("perspective_conditional_utilitarian_deberta_01_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("perspective_conditional_utilitarian_deberta_01_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|perspective_conditional_utilitarian_deberta_01_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/edmundmills/perspective-conditional-utilitarian-deberta-01
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-qa_distell0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-qa_distell0_pipeline_en.md
new file mode 100644
index 00000000000000..3690005d08c191
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-qa_distell0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qa_distell0_pipeline pipeline DistilBertForQuestionAnswering from StaAhmed
+author: John Snow Labs
+name: qa_distell0_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_distell0_pipeline` is a English model originally trained by StaAhmed.
+
+{:.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/qa_distell0_pipeline_en_5.5.0_3.0_1725652452763.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_distell0_pipeline_en_5.5.0_3.0_1725652452763.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
+
+pipeline = PretrainedPipeline("qa_distell0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qa_distell0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_distell0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/StaAhmed/QA_distell0
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-qa_redaction_nov1_18_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-qa_redaction_nov1_18_pipeline_en.md
new file mode 100644
index 00000000000000..54669be1b1af8f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-qa_redaction_nov1_18_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qa_redaction_nov1_18_pipeline pipeline XlmRoBertaForQuestionAnswering from am-infoweb
+author: John Snow Labs
+name: qa_redaction_nov1_18_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_redaction_nov1_18_pipeline` is a English model originally trained by am-infoweb.
+
+{:.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/qa_redaction_nov1_18_pipeline_en_5.5.0_3.0_1725631167369.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_redaction_nov1_18_pipeline_en_5.5.0_3.0_1725631167369.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
+
+pipeline = PretrainedPipeline("qa_redaction_nov1_18_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qa_redaction_nov1_18_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_redaction_nov1_18_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|795.3 MB|
+
+## References
+
+https://huggingface.co/am-infoweb/QA_REDACTION_NOV1_18
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-roberta_babe_ft_en.md b/docs/_posts/ahmedlone127/2024-09-06-roberta_babe_ft_en.md
new file mode 100644
index 00000000000000..e12a7039a35c0a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-roberta_babe_ft_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_babe_ft RoBertaForSequenceClassification from mediabiasgroup
+author: John Snow Labs
+name: roberta_babe_ft
+date: 2024-09-06
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_babe_ft` is a English model originally trained by mediabiasgroup.
+
+{:.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/roberta_babe_ft_en_5.5.0_3.0_1725613450239.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_babe_ft_en_5.5.0_3.0_1725613450239.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta_babe_ft","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_babe_ft", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_babe_ft|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|446.0 MB|
+
+## References
+
+https://huggingface.co/mediabiasgroup/roberta-babe-ft
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-roberta_ner_roberta_large_tweetner_random_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-roberta_ner_roberta_large_tweetner_random_pipeline_en.md
new file mode 100644
index 00000000000000..4ff51c2c09a9a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-roberta_ner_roberta_large_tweetner_random_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_ner_roberta_large_tweetner_random_pipeline pipeline RoBertaForTokenClassification from tner
+author: John Snow Labs
+name: roberta_ner_roberta_large_tweetner_random_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_ner_roberta_large_tweetner_random_pipeline` is a English model originally trained by tner.
+
+{:.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/roberta_ner_roberta_large_tweetner_random_pipeline_en_5.5.0_3.0_1725624988283.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_ner_roberta_large_tweetner_random_pipeline_en_5.5.0_3.0_1725624988283.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
+
+pipeline = PretrainedPipeline("roberta_ner_roberta_large_tweetner_random_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_ner_roberta_large_tweetner_random_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_ner_roberta_large_tweetner_random_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/tner/roberta-large-tweetner-random
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-scenario_non_kd_scr_d2_data_amazonscience_massive_all_1_1_gamma_jason_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-scenario_non_kd_scr_d2_data_amazonscience_massive_all_1_1_gamma_jason_pipeline_en.md
new file mode 100644
index 00000000000000..02506ad87b5677
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-scenario_non_kd_scr_d2_data_amazonscience_massive_all_1_1_gamma_jason_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English scenario_non_kd_scr_d2_data_amazonscience_massive_all_1_1_gamma_jason_pipeline pipeline XlmRoBertaForSequenceClassification from haryoaw
+author: John Snow Labs
+name: scenario_non_kd_scr_d2_data_amazonscience_massive_all_1_1_gamma_jason_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scenario_non_kd_scr_d2_data_amazonscience_massive_all_1_1_gamma_jason_pipeline` is a English model originally trained by haryoaw.
+
+{:.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/scenario_non_kd_scr_d2_data_amazonscience_massive_all_1_1_gamma_jason_pipeline_en_5.5.0_3.0_1725620259720.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scenario_non_kd_scr_d2_data_amazonscience_massive_all_1_1_gamma_jason_pipeline_en_5.5.0_3.0_1725620259720.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
+
+pipeline = PretrainedPipeline("scenario_non_kd_scr_d2_data_amazonscience_massive_all_1_1_gamma_jason_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("scenario_non_kd_scr_d2_data_amazonscience_massive_all_1_1_gamma_jason_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|scenario_non_kd_scr_d2_data_amazonscience_massive_all_1_1_gamma_jason_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|884.3 MB|
+
+## References
+
+https://huggingface.co/haryoaw/scenario-NON-KD-SCR-D2_data-AmazonScience_massive_all_1_1_gamma-jason
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-sent_bert_large_uncased_semeval2014_en.md b/docs/_posts/ahmedlone127/2024-09-06-sent_bert_large_uncased_semeval2014_en.md
new file mode 100644
index 00000000000000..d323f43fc2621b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-sent_bert_large_uncased_semeval2014_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_large_uncased_semeval2014 BertSentenceEmbeddings from StevenLimcorn
+author: John Snow Labs
+name: sent_bert_large_uncased_semeval2014
+date: 2024-09-06
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_large_uncased_semeval2014` is a English model originally trained by StevenLimcorn.
+
+{:.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/sent_bert_large_uncased_semeval2014_en_5.5.0_3.0_1725666932953.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_large_uncased_semeval2014_en_5.5.0_3.0_1725666932953.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_large_uncased_semeval2014","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_large_uncased_semeval2014","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_large_uncased_semeval2014|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/StevenLimcorn/bert-large-uncased-semeval2014
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-sent_cdgp_chilean_sign_language_bert_cloth_en.md b/docs/_posts/ahmedlone127/2024-09-06-sent_cdgp_chilean_sign_language_bert_cloth_en.md
new file mode 100644
index 00000000000000..f6dead25a5cd69
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-sent_cdgp_chilean_sign_language_bert_cloth_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_cdgp_chilean_sign_language_bert_cloth BertSentenceEmbeddings from AndyChiang
+author: John Snow Labs
+name: sent_cdgp_chilean_sign_language_bert_cloth
+date: 2024-09-06
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_cdgp_chilean_sign_language_bert_cloth` is a English model originally trained by AndyChiang.
+
+{:.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/sent_cdgp_chilean_sign_language_bert_cloth_en_5.5.0_3.0_1725666941959.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_cdgp_chilean_sign_language_bert_cloth_en_5.5.0_3.0_1725666941959.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_cdgp_chilean_sign_language_bert_cloth","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_cdgp_chilean_sign_language_bert_cloth","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_cdgp_chilean_sign_language_bert_cloth|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/AndyChiang/cdgp-csg-bert-cloth
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-sent_cdgp_chilean_sign_language_bert_cloth_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-sent_cdgp_chilean_sign_language_bert_cloth_pipeline_en.md
new file mode 100644
index 00000000000000..c81f676cd7ba8e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-sent_cdgp_chilean_sign_language_bert_cloth_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_cdgp_chilean_sign_language_bert_cloth_pipeline pipeline BertSentenceEmbeddings from AndyChiang
+author: John Snow Labs
+name: sent_cdgp_chilean_sign_language_bert_cloth_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_cdgp_chilean_sign_language_bert_cloth_pipeline` is a English model originally trained by AndyChiang.
+
+{:.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/sent_cdgp_chilean_sign_language_bert_cloth_pipeline_en_5.5.0_3.0_1725666962041.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_cdgp_chilean_sign_language_bert_cloth_pipeline_en_5.5.0_3.0_1725666962041.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
+
+pipeline = PretrainedPipeline("sent_cdgp_chilean_sign_language_bert_cloth_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_cdgp_chilean_sign_language_bert_cloth_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_cdgp_chilean_sign_language_bert_cloth_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.6 MB|
+
+## References
+
+https://huggingface.co/AndyChiang/cdgp-csg-bert-cloth
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-sent_hing_mbert_pipeline_hi.md b/docs/_posts/ahmedlone127/2024-09-06-sent_hing_mbert_pipeline_hi.md
new file mode 100644
index 00000000000000..678a4de402b476
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-sent_hing_mbert_pipeline_hi.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Hindi sent_hing_mbert_pipeline pipeline BertSentenceEmbeddings from l3cube-pune
+author: John Snow Labs
+name: sent_hing_mbert_pipeline
+date: 2024-09-06
+tags: [hi, open_source, pipeline, onnx]
+task: Embeddings
+language: hi
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_hing_mbert_pipeline` is a Hindi model originally trained by l3cube-pune.
+
+{:.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/sent_hing_mbert_pipeline_hi_5.5.0_3.0_1725650841315.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_hing_mbert_pipeline_hi_5.5.0_3.0_1725650841315.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
+
+pipeline = PretrainedPipeline("sent_hing_mbert_pipeline", lang = "hi")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_hing_mbert_pipeline", lang = "hi")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_hing_mbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|hi|
+|Size:|665.5 MB|
+
+## References
+
+https://huggingface.co/l3cube-pune/hing-mbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-sent_koobert_xx.md b/docs/_posts/ahmedlone127/2024-09-06-sent_koobert_xx.md
new file mode 100644
index 00000000000000..9e9bf679c193e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-sent_koobert_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual sent_koobert BertSentenceEmbeddings from KooAI
+author: John Snow Labs
+name: sent_koobert
+date: 2024-09-06
+tags: [xx, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_koobert` is a Multilingual model originally trained by KooAI.
+
+{:.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/sent_koobert_xx_5.5.0_3.0_1725651129253.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_koobert_xx_5.5.0_3.0_1725651129253.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_koobert","xx") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_koobert","xx") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_koobert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|xx|
+|Size:|689.1 MB|
+
+## References
+
+https://huggingface.co/KooAI/KooBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-sent_neural_cherche_sparse_embed_en.md b/docs/_posts/ahmedlone127/2024-09-06-sent_neural_cherche_sparse_embed_en.md
new file mode 100644
index 00000000000000..f30766cb93e986
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-sent_neural_cherche_sparse_embed_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_neural_cherche_sparse_embed BertSentenceEmbeddings from raphaelsty
+author: John Snow Labs
+name: sent_neural_cherche_sparse_embed
+date: 2024-09-06
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_neural_cherche_sparse_embed` is a English model originally trained by raphaelsty.
+
+{:.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/sent_neural_cherche_sparse_embed_en_5.5.0_3.0_1725650922628.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_neural_cherche_sparse_embed_en_5.5.0_3.0_1725650922628.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_neural_cherche_sparse_embed","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_neural_cherche_sparse_embed","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_neural_cherche_sparse_embed|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.4 MB|
+
+## References
+
+https://huggingface.co/raphaelsty/neural-cherche-sparse-embed
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-sent_xlm_roberta_base_finetuned_yoruba_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-sent_xlm_roberta_base_finetuned_yoruba_pipeline_en.md
new file mode 100644
index 00000000000000..50240b3c3c66c6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-sent_xlm_roberta_base_finetuned_yoruba_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_yoruba_pipeline pipeline XlmRoBertaSentenceEmbeddings from Davlan
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_yoruba_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_finetuned_yoruba_pipeline` is a English model originally trained by Davlan.
+
+{:.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/sent_xlm_roberta_base_finetuned_yoruba_pipeline_en_5.5.0_3.0_1725623512196.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_yoruba_pipeline_en_5.5.0_3.0_1725623512196.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
+
+pipeline = PretrainedPipeline("sent_xlm_roberta_base_finetuned_yoruba_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_xlm_roberta_base_finetuned_yoruba_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_yoruba_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-yoruba
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-southern_sotho_all_mpnet_finetuned_arabic_1500_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-southern_sotho_all_mpnet_finetuned_arabic_1500_pipeline_en.md
new file mode 100644
index 00000000000000..b6b3b336dcdace
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-southern_sotho_all_mpnet_finetuned_arabic_1500_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English southern_sotho_all_mpnet_finetuned_arabic_1500_pipeline pipeline MPNetEmbeddings from danfeg
+author: John Snow Labs
+name: southern_sotho_all_mpnet_finetuned_arabic_1500_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`southern_sotho_all_mpnet_finetuned_arabic_1500_pipeline` is a English model originally trained by danfeg.
+
+{:.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/southern_sotho_all_mpnet_finetuned_arabic_1500_pipeline_en_5.5.0_3.0_1725595731988.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/southern_sotho_all_mpnet_finetuned_arabic_1500_pipeline_en_5.5.0_3.0_1725595731988.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
+
+pipeline = PretrainedPipeline("southern_sotho_all_mpnet_finetuned_arabic_1500_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("southern_sotho_all_mpnet_finetuned_arabic_1500_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|southern_sotho_all_mpnet_finetuned_arabic_1500_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/danfeg/ST-ALL-MPNET_Finetuned-AR-1500
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-t2t_gun_nlth_from_base_warmup_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-t2t_gun_nlth_from_base_warmup_pipeline_en.md
new file mode 100644
index 00000000000000..e2152c34cea478
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-t2t_gun_nlth_from_base_warmup_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English t2t_gun_nlth_from_base_warmup_pipeline pipeline MarianTransformer from tiagoblima
+author: John Snow Labs
+name: t2t_gun_nlth_from_base_warmup_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`t2t_gun_nlth_from_base_warmup_pipeline` is a English model originally trained by tiagoblima.
+
+{:.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/t2t_gun_nlth_from_base_warmup_pipeline_en_5.5.0_3.0_1725636169094.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/t2t_gun_nlth_from_base_warmup_pipeline_en_5.5.0_3.0_1725636169094.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
+
+pipeline = PretrainedPipeline("t2t_gun_nlth_from_base_warmup_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("t2t_gun_nlth_from_base_warmup_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|t2t_gun_nlth_from_base_warmup_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|220.9 MB|
+
+## References
+
+https://huggingface.co/tiagoblima/t2t-gun-nlth-from-base-warmup
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-tb_xlm_r_fpt_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-tb_xlm_r_fpt_pipeline_en.md
new file mode 100644
index 00000000000000..a33f96f4dcf407
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-tb_xlm_r_fpt_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English tb_xlm_r_fpt_pipeline pipeline XlmRoBertaEmbeddings from aplycaebous
+author: John Snow Labs
+name: tb_xlm_r_fpt_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tb_xlm_r_fpt_pipeline` is a English model originally trained by aplycaebous.
+
+{:.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/tb_xlm_r_fpt_pipeline_en_5.5.0_3.0_1725596576772.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tb_xlm_r_fpt_pipeline_en_5.5.0_3.0_1725596576772.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
+
+pipeline = PretrainedPipeline("tb_xlm_r_fpt_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tb_xlm_r_fpt_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tb_xlm_r_fpt_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/aplycaebous/tb-XLM-R-fpt
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-tcfd_recommendation_classifier_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-tcfd_recommendation_classifier_v1_pipeline_en.md
new file mode 100644
index 00000000000000..d492b0efd5be1f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-tcfd_recommendation_classifier_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English tcfd_recommendation_classifier_v1_pipeline pipeline DistilBertForSequenceClassification from SonnyB
+author: John Snow Labs
+name: tcfd_recommendation_classifier_v1_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tcfd_recommendation_classifier_v1_pipeline` is a English model originally trained by SonnyB.
+
+{:.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/tcfd_recommendation_classifier_v1_pipeline_en_5.5.0_3.0_1725608635047.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tcfd_recommendation_classifier_v1_pipeline_en_5.5.0_3.0_1725608635047.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
+
+pipeline = PretrainedPipeline("tcfd_recommendation_classifier_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tcfd_recommendation_classifier_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tcfd_recommendation_classifier_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/SonnyB/tcfd_recommendation_classifier_v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-test_with_web_interface_en.md b/docs/_posts/ahmedlone127/2024-09-06-test_with_web_interface_en.md
new file mode 100644
index 00000000000000..c2cc8fcab1cc1d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-test_with_web_interface_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English test_with_web_interface CamemBertEmbeddings from Hasanmurad
+author: John Snow Labs
+name: test_with_web_interface
+date: 2024-09-06
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_with_web_interface` is a English model originally trained by Hasanmurad.
+
+{:.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/test_with_web_interface_en_5.5.0_3.0_1725637081717.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_with_web_interface_en_5.5.0_3.0_1725637081717.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("test_with_web_interface","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("test_with_web_interface","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_with_web_interface|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Hasanmurad/test_with_web_interface
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-testarbaraz_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-testarbaraz_pipeline_en.md
new file mode 100644
index 00000000000000..7995bd7ea31094
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-testarbaraz_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English testarbaraz_pipeline pipeline DistilBertForQuestionAnswering from kevinbram
+author: John Snow Labs
+name: testarbaraz_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`testarbaraz_pipeline` is a English model originally trained by kevinbram.
+
+{:.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/testarbaraz_pipeline_en_5.5.0_3.0_1725654590666.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/testarbaraz_pipeline_en_5.5.0_3.0_1725654590666.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
+
+pipeline = PretrainedPipeline("testarbaraz_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("testarbaraz_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|testarbaraz_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/kevinbram/testarbaraz
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-testarenz_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-testarenz_pipeline_en.md
new file mode 100644
index 00000000000000..09b4dc483f1889
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-testarenz_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English testarenz_pipeline pipeline DistilBertForQuestionAnswering from kevinbram
+author: John Snow Labs
+name: testarenz_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`testarenz_pipeline` is a English model originally trained by kevinbram.
+
+{:.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/testarenz_pipeline_en_5.5.0_3.0_1725654732298.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/testarenz_pipeline_en_5.5.0_3.0_1725654732298.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
+
+pipeline = PretrainedPipeline("testarenz_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("testarenz_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|testarenz_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/kevinbram/testarenz
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-tiny_bert_0102_last_iter_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-tiny_bert_0102_last_iter_pipeline_en.md
new file mode 100644
index 00000000000000..4be71284faeace
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-tiny_bert_0102_last_iter_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English tiny_bert_0102_last_iter_pipeline pipeline AlbertForSequenceClassification from gg-ai
+author: John Snow Labs
+name: tiny_bert_0102_last_iter_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_bert_0102_last_iter_pipeline` is a English model originally trained by gg-ai.
+
+{:.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/tiny_bert_0102_last_iter_pipeline_en_5.5.0_3.0_1725628376798.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_bert_0102_last_iter_pipeline_en_5.5.0_3.0_1725628376798.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
+
+pipeline = PretrainedPipeline("tiny_bert_0102_last_iter_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tiny_bert_0102_last_iter_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tiny_bert_0102_last_iter_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|20.5 MB|
+
+## References
+
+https://huggingface.co/gg-ai/tiny-bert-0102-last-iter
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-topic_topic_random0_seed2_bernice_en.md b/docs/_posts/ahmedlone127/2024-09-06-topic_topic_random0_seed2_bernice_en.md
new file mode 100644
index 00000000000000..7f112dc5ccdb21
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-topic_topic_random0_seed2_bernice_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English topic_topic_random0_seed2_bernice XlmRoBertaForSequenceClassification from tweettemposhift
+author: John Snow Labs
+name: topic_topic_random0_seed2_bernice
+date: 2024-09-06
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`topic_topic_random0_seed2_bernice` is a English model originally trained by tweettemposhift.
+
+{:.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/topic_topic_random0_seed2_bernice_en_5.5.0_3.0_1725620455375.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/topic_topic_random0_seed2_bernice_en_5.5.0_3.0_1725620455375.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("topic_topic_random0_seed2_bernice","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("topic_topic_random0_seed2_bernice", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|topic_topic_random0_seed2_bernice|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|805.5 MB|
+
+## References
+
+https://huggingface.co/tweettemposhift/topic-topic_random0_seed2-bernice
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-trained_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-trained_english_pipeline_en.md
new file mode 100644
index 00000000000000..7e219c598bd6f4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-trained_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English trained_english_pipeline pipeline DistilBertForTokenClassification from annamariagnat
+author: John Snow Labs
+name: trained_english_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trained_english_pipeline` is a English model originally trained by annamariagnat.
+
+{:.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/trained_english_pipeline_en_5.5.0_3.0_1725599542859.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trained_english_pipeline_en_5.5.0_3.0_1725599542859.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
+
+pipeline = PretrainedPipeline("trained_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("trained_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trained_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/annamariagnat/trained_english
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-useless_model_try_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-useless_model_try_1_pipeline_en.md
new file mode 100644
index 00000000000000..4ff43399c853b6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-useless_model_try_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English useless_model_try_1_pipeline pipeline RoBertaForSequenceClassification from timoneda
+author: John Snow Labs
+name: useless_model_try_1_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`useless_model_try_1_pipeline` is a English model originally trained by timoneda.
+
+{:.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/useless_model_try_1_pipeline_en_5.5.0_3.0_1725612935042.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/useless_model_try_1_pipeline_en_5.5.0_3.0_1725612935042.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
+
+pipeline = PretrainedPipeline("useless_model_try_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("useless_model_try_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|useless_model_try_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/timoneda/useless_model_try_1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-whisper_small_indonesian_cv17_en.md b/docs/_posts/ahmedlone127/2024-09-06-whisper_small_indonesian_cv17_en.md
new file mode 100644
index 00000000000000..b58a2506bb7bd8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-whisper_small_indonesian_cv17_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English whisper_small_indonesian_cv17 WhisperForCTC from Bagus
+author: John Snow Labs
+name: whisper_small_indonesian_cv17
+date: 2024-09-06
+tags: [en, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_indonesian_cv17` is a English model originally trained by Bagus.
+
+{:.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/whisper_small_indonesian_cv17_en_5.5.0_3.0_1725645945070.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_indonesian_cv17_en_5.5.0_3.0_1725645945070.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
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_small_indonesian_cv17","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_small_indonesian_cv17", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_indonesian_cv17|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/Bagus/whisper-small-id-cv17
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-whisper_small_korean_haseong8012_pipeline_ko.md b/docs/_posts/ahmedlone127/2024-09-06-whisper_small_korean_haseong8012_pipeline_ko.md
new file mode 100644
index 00000000000000..4c328cbe02b265
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-whisper_small_korean_haseong8012_pipeline_ko.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Korean whisper_small_korean_haseong8012_pipeline pipeline WhisperForCTC from haseong8012
+author: John Snow Labs
+name: whisper_small_korean_haseong8012_pipeline
+date: 2024-09-06
+tags: [ko, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: ko
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_korean_haseong8012_pipeline` is a Korean model originally trained by haseong8012.
+
+{:.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/whisper_small_korean_haseong8012_pipeline_ko_5.5.0_3.0_1725644662891.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_korean_haseong8012_pipeline_ko_5.5.0_3.0_1725644662891.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
+
+pipeline = PretrainedPipeline("whisper_small_korean_haseong8012_pipeline", lang = "ko")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_small_korean_haseong8012_pipeline", lang = "ko")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_korean_haseong8012_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ko|
+|Size:|642.4 MB|
+
+## References
+
+https://huggingface.co/haseong8012/whisper-small-ko
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-whisper_small_spanish_nemo_unified_2024_07_02_15_19_06_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-whisper_small_spanish_nemo_unified_2024_07_02_15_19_06_pipeline_en.md
new file mode 100644
index 00000000000000..43abf36eca60fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-whisper_small_spanish_nemo_unified_2024_07_02_15_19_06_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English whisper_small_spanish_nemo_unified_2024_07_02_15_19_06_pipeline pipeline WhisperForCTC from sgonzalezsilot
+author: John Snow Labs
+name: whisper_small_spanish_nemo_unified_2024_07_02_15_19_06_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_spanish_nemo_unified_2024_07_02_15_19_06_pipeline` is a English model originally trained by sgonzalezsilot.
+
+{:.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/whisper_small_spanish_nemo_unified_2024_07_02_15_19_06_pipeline_en_5.5.0_3.0_1725586840143.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_spanish_nemo_unified_2024_07_02_15_19_06_pipeline_en_5.5.0_3.0_1725586840143.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
+
+pipeline = PretrainedPipeline("whisper_small_spanish_nemo_unified_2024_07_02_15_19_06_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_small_spanish_nemo_unified_2024_07_02_15_19_06_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_spanish_nemo_unified_2024_07_02_15_19_06_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/sgonzalezsilot/whisper-small-es-Nemo_unified_2024-07-02_15-19-06
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-whisper_tiny_korean_ko.md b/docs/_posts/ahmedlone127/2024-09-06-whisper_tiny_korean_ko.md
new file mode 100644
index 00000000000000..7779e618f5bc5a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-whisper_tiny_korean_ko.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Korean whisper_tiny_korean WhisperForCTC from TheoJo
+author: John Snow Labs
+name: whisper_tiny_korean
+date: 2024-09-06
+tags: [ko, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: ko
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_tiny_korean` is a Korean model originally trained by TheoJo.
+
+{:.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/whisper_tiny_korean_ko_5.5.0_3.0_1725604785697.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_korean_ko_5.5.0_3.0_1725604785697.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
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_tiny_korean","ko") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_tiny_korean", "ko")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_tiny_korean|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|ko|
+|Size:|242.8 MB|
+
+## References
+
+https://huggingface.co/TheoJo/whisper-tiny-ko
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-working_en.md b/docs/_posts/ahmedlone127/2024-09-06-working_en.md
new file mode 100644
index 00000000000000..57df9ed63562b8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-working_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English working DistilBertForQuestionAnswering from mahiram
+author: John Snow Labs
+name: working
+date: 2024-09-06
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`working` is a English model originally trained by mahiram.
+
+{:.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/working_en_5.5.0_3.0_1725654384520.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/working_en_5.5.0_3.0_1725654384520.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("working","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("working", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|working|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/mahiram/working
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-working_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-working_pipeline_en.md
new file mode 100644
index 00000000000000..a2bf410be455ea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-working_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English working_pipeline pipeline DistilBertForQuestionAnswering from mahiram
+author: John Snow Labs
+name: working_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`working_pipeline` is a English model originally trained by mahiram.
+
+{:.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/working_pipeline_en_5.5.0_3.0_1725654396420.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/working_pipeline_en_5.5.0_3.0_1725654396420.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
+
+pipeline = PretrainedPipeline("working_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("working_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|working_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/mahiram/working
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-xlm_roberta_base_germeval21_toxic_with_data_augmentation_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-xlm_roberta_base_germeval21_toxic_with_data_augmentation_pipeline_en.md
new file mode 100644
index 00000000000000..d7e1852e0aeb4e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-xlm_roberta_base_germeval21_toxic_with_data_augmentation_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_germeval21_toxic_with_data_augmentation_pipeline pipeline XlmRoBertaForSequenceClassification from airKlizz
+author: John Snow Labs
+name: xlm_roberta_base_germeval21_toxic_with_data_augmentation_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_germeval21_toxic_with_data_augmentation_pipeline` is a English model originally trained by airKlizz.
+
+{:.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/xlm_roberta_base_germeval21_toxic_with_data_augmentation_pipeline_en_5.5.0_3.0_1725619660571.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_germeval21_toxic_with_data_augmentation_pipeline_en_5.5.0_3.0_1725619660571.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_germeval21_toxic_with_data_augmentation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_germeval21_toxic_with_data_augmentation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_germeval21_toxic_with_data_augmentation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|790.0 MB|
+
+## References
+
+https://huggingface.co/airKlizz/xlm-roberta-base-germeval21-toxic-with-data-augmentation
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-xlm_roberta_base_wolof_en.md b/docs/_posts/ahmedlone127/2024-09-06-xlm_roberta_base_wolof_en.md
new file mode 100644
index 00000000000000..a3a5db845ee25e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-xlm_roberta_base_wolof_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_wolof XlmRoBertaForTokenClassification from vonewman
+author: John Snow Labs
+name: xlm_roberta_base_wolof
+date: 2024-09-06
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_wolof` is a English model originally trained by vonewman.
+
+{:.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/xlm_roberta_base_wolof_en_5.5.0_3.0_1725658394873.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_wolof_en_5.5.0_3.0_1725658394873.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_wolof","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_wolof", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_wolof|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|777.5 MB|
+
+## References
+
+https://huggingface.co/vonewman/xlm-roberta-base-wolof
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-xlmroberta_ner_haesun_base_finetuned_panx_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-06-xlmroberta_ner_haesun_base_finetuned_panx_pipeline_en.md
new file mode 100644
index 00000000000000..c51fc5f031a5e2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-xlmroberta_ner_haesun_base_finetuned_panx_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlmroberta_ner_haesun_base_finetuned_panx_pipeline pipeline XlmRoBertaForTokenClassification from haesun
+author: John Snow Labs
+name: xlmroberta_ner_haesun_base_finetuned_panx_pipeline
+date: 2024-09-06
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_haesun_base_finetuned_panx_pipeline` is a English model originally trained by haesun.
+
+{:.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/xlmroberta_ner_haesun_base_finetuned_panx_pipeline_en_5.5.0_3.0_1725592628686.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_haesun_base_finetuned_panx_pipeline_en_5.5.0_3.0_1725592628686.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
+
+pipeline = PretrainedPipeline("xlmroberta_ner_haesun_base_finetuned_panx_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_haesun_base_finetuned_panx_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_haesun_base_finetuned_panx_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/haesun/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-06-xlmroberta_ner_olpa_base_finetuned_panx_de.md b/docs/_posts/ahmedlone127/2024-09-06-xlmroberta_ner_olpa_base_finetuned_panx_de.md
new file mode 100644
index 00000000000000..11cda584bd1ca6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-06-xlmroberta_ner_olpa_base_finetuned_panx_de.md
@@ -0,0 +1,113 @@
+---
+layout: model
+title: German XLMRobertaForTokenClassification Base Cased model (from olpa)
+author: John Snow Labs
+name: xlmroberta_ner_olpa_base_finetuned_panx
+date: 2024-09-06
+tags: [de, open_source, xlm_roberta, ner, onnx]
+task: Named Entity Recognition
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-panx-de` is a German model originally trained by `olpa`.
+
+## Predicted Entities
+
+`PER`, `LOC`, `ORG`
+
+{:.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/xlmroberta_ner_olpa_base_finetuned_panx_de_5.5.0_3.0_1725591732670.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_olpa_base_finetuned_panx_de_5.5.0_3.0_1725591732670.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
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_olpa_base_finetuned_panx","de") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+ner_converter = NerConverter()\
+    .setInputCols(["document", "token", "ner"])\
+    .setOutputCol("ner_chunk")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+      .setInputCols(Array("text"))
+      .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_olpa_base_finetuned_panx","de")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val ner_converter = new NerConverter()
+    .setInputCols(Array("document", "token', "ner"))
+    .setOutputCol("ner_chunk")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("de.ner.xlmr_roberta.xtreme.base_finetuned.by_olpa").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_olpa_base_finetuned_panx|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|de|
+|Size:|853.8 MB|
+
+## References
+
+References
+
+- https://huggingface.co/olpa/xlm-roberta-base-finetuned-panx-de
+- https://paperswithcode.com/sota?task=Token+Classification&dataset=xtreme
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-4_datasets_fake_news_with_balanced_with_add_one_sentence_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-4_datasets_fake_news_with_balanced_with_add_one_sentence_pipeline_en.md
new file mode 100644
index 00000000000000..5585097d2a0642
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-4_datasets_fake_news_with_balanced_with_add_one_sentence_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English 4_datasets_fake_news_with_balanced_with_add_one_sentence_pipeline pipeline DistilBertForSequenceClassification from littlepinhorse
+author: John Snow Labs
+name: 4_datasets_fake_news_with_balanced_with_add_one_sentence_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`4_datasets_fake_news_with_balanced_with_add_one_sentence_pipeline` is a English model originally trained by littlepinhorse.
+
+{:.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/4_datasets_fake_news_with_balanced_with_add_one_sentence_pipeline_en_5.5.0_3.0_1725674973884.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/4_datasets_fake_news_with_balanced_with_add_one_sentence_pipeline_en_5.5.0_3.0_1725674973884.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
+
+pipeline = PretrainedPipeline("4_datasets_fake_news_with_balanced_with_add_one_sentence_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("4_datasets_fake_news_with_balanced_with_add_one_sentence_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|4_datasets_fake_news_with_balanced_with_add_one_sentence_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/littlepinhorse/4_datasets_fake_news_with_Balanced_With_add_one_sentence
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-adress_parser_model_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-adress_parser_model_2_pipeline_en.md
new file mode 100644
index 00000000000000..2e7fe3d87633a7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-adress_parser_model_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English adress_parser_model_2_pipeline pipeline DistilBertForTokenClassification from ManuelMM
+author: John Snow Labs
+name: adress_parser_model_2_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`adress_parser_model_2_pipeline` is a English model originally trained by ManuelMM.
+
+{:.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/adress_parser_model_2_pipeline_en_5.5.0_3.0_1725731212440.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/adress_parser_model_2_pipeline_en_5.5.0_3.0_1725731212440.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
+
+pipeline = PretrainedPipeline("adress_parser_model_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("adress_parser_model_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|adress_parser_model_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/ManuelMM/adress_parser_model_2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-adress_parser_model_epochs_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-adress_parser_model_epochs_pipeline_en.md
new file mode 100644
index 00000000000000..38970c29256595
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-adress_parser_model_epochs_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English adress_parser_model_epochs_pipeline pipeline DistilBertForTokenClassification from ManuelMM
+author: John Snow Labs
+name: adress_parser_model_epochs_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`adress_parser_model_epochs_pipeline` is a English model originally trained by ManuelMM.
+
+{:.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/adress_parser_model_epochs_pipeline_en_5.5.0_3.0_1725730537684.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/adress_parser_model_epochs_pipeline_en_5.5.0_3.0_1725730537684.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
+
+pipeline = PretrainedPipeline("adress_parser_model_epochs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("adress_parser_model_epochs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|adress_parser_model_epochs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/ManuelMM/adress_parser_model_epochs
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-agric_eng_lug_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-agric_eng_lug_pipeline_en.md
new file mode 100644
index 00000000000000..4ca73cfb6a3a4a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-agric_eng_lug_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English agric_eng_lug_pipeline pipeline MarianTransformer from hellennamulinda
+author: John Snow Labs
+name: agric_eng_lug_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`agric_eng_lug_pipeline` is a English model originally trained by hellennamulinda.
+
+{:.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/agric_eng_lug_pipeline_en_5.5.0_3.0_1725746756152.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/agric_eng_lug_pipeline_en_5.5.0_3.0_1725746756152.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
+
+pipeline = PretrainedPipeline("agric_eng_lug_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("agric_eng_lug_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|agric_eng_lug_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|530.8 MB|
+
+## References
+
+https://huggingface.co/hellennamulinda/agric-eng-lug
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-albert_tiny_chinese_david_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-albert_tiny_chinese_david_ner_pipeline_en.md
new file mode 100644
index 00000000000000..6dad47da1968cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-albert_tiny_chinese_david_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English albert_tiny_chinese_david_ner_pipeline pipeline BertForTokenClassification from davidliu1110
+author: John Snow Labs
+name: albert_tiny_chinese_david_ner_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_tiny_chinese_david_ner_pipeline` is a English model originally trained by davidliu1110.
+
+{:.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/albert_tiny_chinese_david_ner_pipeline_en_5.5.0_3.0_1725734969766.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_tiny_chinese_david_ner_pipeline_en_5.5.0_3.0_1725734969766.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
+
+pipeline = PretrainedPipeline("albert_tiny_chinese_david_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_tiny_chinese_david_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_tiny_chinese_david_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|15.1 MB|
+
+## References
+
+https://huggingface.co/davidliu1110/albert-tiny-chinese-david-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-aliens_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-aliens_pipeline_en.md
new file mode 100644
index 00000000000000..434c72fa921e66
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-aliens_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English aliens_pipeline pipeline DistilBertForSequenceClassification from arkalon
+author: John Snow Labs
+name: aliens_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`aliens_pipeline` is a English model originally trained by arkalon.
+
+{:.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/aliens_pipeline_en_5.5.0_3.0_1725674624843.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/aliens_pipeline_en_5.5.0_3.0_1725674624843.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
+
+pipeline = PretrainedPipeline("aliens_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("aliens_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|aliens_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/arkalon/aliens
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-all_mpnet_base_v2_20240102_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-all_mpnet_base_v2_20240102_pipeline_en.md
new file mode 100644
index 00000000000000..013dbec9df04c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-all_mpnet_base_v2_20240102_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English all_mpnet_base_v2_20240102_pipeline pipeline MPNetForSequenceClassification from Kevinger
+author: John Snow Labs
+name: all_mpnet_base_v2_20240102_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_20240102_pipeline` is a English model originally trained by Kevinger.
+
+{:.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/all_mpnet_base_v2_20240102_pipeline_en_5.5.0_3.0_1725733242060.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_20240102_pipeline_en_5.5.0_3.0_1725733242060.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
+
+pipeline = PretrainedPipeline("all_mpnet_base_v2_20240102_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_mpnet_base_v2_20240102_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_mpnet_base_v2_20240102_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.2 MB|
+
+## References
+
+https://huggingface.co/Kevinger/all-mpnet-base-v2-20240102
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- MPNetForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-argumentmining_english_iloko_aif_roberta_l_en.md b/docs/_posts/ahmedlone127/2024-09-07-argumentmining_english_iloko_aif_roberta_l_en.md
new file mode 100644
index 00000000000000..5b6eb703420724
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-argumentmining_english_iloko_aif_roberta_l_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English argumentmining_english_iloko_aif_roberta_l RoBertaForSequenceClassification from raruidol
+author: John Snow Labs
+name: argumentmining_english_iloko_aif_roberta_l
+date: 2024-09-07
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`argumentmining_english_iloko_aif_roberta_l` is a English model originally trained by raruidol.
+
+{:.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/argumentmining_english_iloko_aif_roberta_l_en_5.5.0_3.0_1725718349091.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/argumentmining_english_iloko_aif_roberta_l_en_5.5.0_3.0_1725718349091.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("argumentmining_english_iloko_aif_roberta_l","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("argumentmining_english_iloko_aif_roberta_l", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|argumentmining_english_iloko_aif_roberta_l|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/raruidol/ArgumentMining-EN-ILO-AIF-RoBERTa_L
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-attribute_mining_mslacerda_en.md b/docs/_posts/ahmedlone127/2024-09-07-attribute_mining_mslacerda_en.md
new file mode 100644
index 00000000000000..e2b95d7a369b4f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-attribute_mining_mslacerda_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English attribute_mining_mslacerda DistilBertForTokenClassification from MSLacerda
+author: John Snow Labs
+name: attribute_mining_mslacerda
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`attribute_mining_mslacerda` is a English model originally trained by MSLacerda.
+
+{:.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/attribute_mining_mslacerda_en_5.5.0_3.0_1725729891013.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/attribute_mining_mslacerda_en_5.5.0_3.0_1725729891013.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("attribute_mining_mslacerda","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("attribute_mining_mslacerda", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|attribute_mining_mslacerda|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.6 MB|
+
+## References
+
+https://huggingface.co/MSLacerda/attribute_mining_mslacerda
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-attribute_mining_mslacerda_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-attribute_mining_mslacerda_pipeline_en.md
new file mode 100644
index 00000000000000..11d3d699aa0bae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-attribute_mining_mslacerda_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English attribute_mining_mslacerda_pipeline pipeline DistilBertForTokenClassification from MSLacerda
+author: John Snow Labs
+name: attribute_mining_mslacerda_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`attribute_mining_mslacerda_pipeline` is a English model originally trained by MSLacerda.
+
+{:.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/attribute_mining_mslacerda_pipeline_en_5.5.0_3.0_1725729904220.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/attribute_mining_mslacerda_pipeline_en_5.5.0_3.0_1725729904220.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
+
+pipeline = PretrainedPipeline("attribute_mining_mslacerda_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("attribute_mining_mslacerda_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|attribute_mining_mslacerda_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.6 MB|
+
+## References
+
+https://huggingface.co/MSLacerda/attribute_mining_mslacerda
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-augmented_distillbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-augmented_distillbert_pipeline_en.md
new file mode 100644
index 00000000000000..44c9ba390bbc4f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-augmented_distillbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English augmented_distillbert_pipeline pipeline DistilBertForSequenceClassification from erostrate9
+author: John Snow Labs
+name: augmented_distillbert_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`augmented_distillbert_pipeline` is a English model originally trained by erostrate9.
+
+{:.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/augmented_distillbert_pipeline_en_5.5.0_3.0_1725675159286.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/augmented_distillbert_pipeline_en_5.5.0_3.0_1725675159286.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
+
+pipeline = PretrainedPipeline("augmented_distillbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("augmented_distillbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|augmented_distillbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/erostrate9/augmented_distillbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-autotrain_qna_1170143354_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-autotrain_qna_1170143354_pipeline_en.md
new file mode 100644
index 00000000000000..50e264475c6d67
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-autotrain_qna_1170143354_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English autotrain_qna_1170143354_pipeline pipeline DistilBertForQuestionAnswering from IDL
+author: John Snow Labs
+name: autotrain_qna_1170143354_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_qna_1170143354_pipeline` is a English model originally trained by IDL.
+
+{:.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/autotrain_qna_1170143354_pipeline_en_5.5.0_3.0_1725745612560.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_qna_1170143354_pipeline_en_5.5.0_3.0_1725745612560.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
+
+pipeline = PretrainedPipeline("autotrain_qna_1170143354_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("autotrain_qna_1170143354_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_qna_1170143354_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/IDL/autotrain-qna-1170143354
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-benjys_first_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-benjys_first_model_pipeline_en.md
new file mode 100644
index 00000000000000..69ebc2d6530727
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-benjys_first_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English benjys_first_model_pipeline pipeline CamemBertEmbeddings from benyjaykay
+author: John Snow Labs
+name: benjys_first_model_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`benjys_first_model_pipeline` is a English model originally trained by benyjaykay.
+
+{:.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/benjys_first_model_pipeline_en_5.5.0_3.0_1725691364073.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/benjys_first_model_pipeline_en_5.5.0_3.0_1725691364073.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
+
+pipeline = PretrainedPipeline("benjys_first_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("benjys_first_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|benjys_first_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/benyjaykay/benjys-first-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-bert_b09_en.md b/docs/_posts/ahmedlone127/2024-09-07-bert_b09_en.md
new file mode 100644
index 00000000000000..bce4ca4647a29c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-bert_b09_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_b09 DistilBertForTokenClassification from LazzeKappa
+author: John Snow Labs
+name: bert_b09
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_b09` is a English model originally trained by LazzeKappa.
+
+{:.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/bert_b09_en_5.5.0_3.0_1725734329915.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_b09_en_5.5.0_3.0_1725734329915.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("bert_b09","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("bert_b09", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_b09|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/LazzeKappa/BERT_B09
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-bert_b09_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-bert_b09_pipeline_en.md
new file mode 100644
index 00000000000000..0ab9ba591e07bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-bert_b09_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_b09_pipeline pipeline DistilBertForTokenClassification from LazzeKappa
+author: John Snow Labs
+name: bert_b09_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_b09_pipeline` is a English model originally trained by LazzeKappa.
+
+{:.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/bert_b09_pipeline_en_5.5.0_3.0_1725734353555.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_b09_pipeline_en_5.5.0_3.0_1725734353555.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
+
+pipeline = PretrainedPipeline("bert_b09_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_b09_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_b09_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|505.5 MB|
+
+## References
+
+https://huggingface.co/LazzeKappa/BERT_B09
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-bert_finetuned_ner_skyimple_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-bert_finetuned_ner_skyimple_pipeline_en.md
new file mode 100644
index 00000000000000..37361658c824dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-bert_finetuned_ner_skyimple_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_ner_skyimple_pipeline pipeline BertForTokenClassification from skyimple
+author: John Snow Labs
+name: bert_finetuned_ner_skyimple_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_skyimple_pipeline` is a English model originally trained by skyimple.
+
+{:.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/bert_finetuned_ner_skyimple_pipeline_en_5.5.0_3.0_1725734829323.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_skyimple_pipeline_en_5.5.0_3.0_1725734829323.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
+
+pipeline = PretrainedPipeline("bert_finetuned_ner_skyimple_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_ner_skyimple_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_skyimple_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/skyimple/bert-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-bert_finetuned_squad_chaii_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-bert_finetuned_squad_chaii_pipeline_en.md
new file mode 100644
index 00000000000000..0f0bcd6c9be817
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-bert_finetuned_squad_chaii_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_finetuned_squad_chaii_pipeline pipeline XlmRoBertaForQuestionAnswering from SmartPy
+author: John Snow Labs
+name: bert_finetuned_squad_chaii_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_chaii_pipeline` is a English model originally trained by SmartPy.
+
+{:.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/bert_finetuned_squad_chaii_pipeline_en_5.5.0_3.0_1725685850790.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_chaii_pipeline_en_5.5.0_3.0_1725685850790.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
+
+pipeline = PretrainedPipeline("bert_finetuned_squad_chaii_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_squad_chaii_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_squad_chaii_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|886.7 MB|
+
+## References
+
+https://huggingface.co/SmartPy/bert-finetuned-squad-chaii
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-bert_qa_model_jahanzeb1_en.md b/docs/_posts/ahmedlone127/2024-09-07-bert_qa_model_jahanzeb1_en.md
new file mode 100644
index 00000000000000..2b3f3ebe3b5087
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-bert_qa_model_jahanzeb1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bert_qa_model_jahanzeb1 DistilBertForQuestionAnswering from Jahanzeb1
+author: John Snow Labs
+name: bert_qa_model_jahanzeb1
+date: 2024-09-07
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_qa_model_jahanzeb1` is a English model originally trained by Jahanzeb1.
+
+{:.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/bert_qa_model_jahanzeb1_en_5.5.0_3.0_1725695553119.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_model_jahanzeb1_en_5.5.0_3.0_1725695553119.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("bert_qa_model_jahanzeb1","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("bert_qa_model_jahanzeb1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_model_jahanzeb1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Jahanzeb1/BERT_QA_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-bert_wnut_token_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-bert_wnut_token_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..af7a22b92344f8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-bert_wnut_token_classifier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_wnut_token_classifier_pipeline pipeline DistilBertForTokenClassification from ZappY-AI
+author: John Snow Labs
+name: bert_wnut_token_classifier_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_wnut_token_classifier_pipeline` is a English model originally trained by ZappY-AI.
+
+{:.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/bert_wnut_token_classifier_pipeline_en_5.5.0_3.0_1725729884451.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_wnut_token_classifier_pipeline_en_5.5.0_3.0_1725729884451.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
+
+pipeline = PretrainedPipeline("bert_wnut_token_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_wnut_token_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_wnut_token_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/ZappY-AI/bert-wnut-token-classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-bislama_all_bs160_allneg_finetuned_webnlg2020_correctness_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-bislama_all_bs160_allneg_finetuned_webnlg2020_correctness_pipeline_en.md
new file mode 100644
index 00000000000000..e063feacc638c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-bislama_all_bs160_allneg_finetuned_webnlg2020_correctness_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bislama_all_bs160_allneg_finetuned_webnlg2020_correctness_pipeline pipeline MPNetEmbeddings from teven
+author: John Snow Labs
+name: bislama_all_bs160_allneg_finetuned_webnlg2020_correctness_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bislama_all_bs160_allneg_finetuned_webnlg2020_correctness_pipeline` is a English model originally trained by teven.
+
+{:.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/bislama_all_bs160_allneg_finetuned_webnlg2020_correctness_pipeline_en_5.5.0_3.0_1725703588691.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bislama_all_bs160_allneg_finetuned_webnlg2020_correctness_pipeline_en_5.5.0_3.0_1725703588691.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
+
+pipeline = PretrainedPipeline("bislama_all_bs160_allneg_finetuned_webnlg2020_correctness_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bislama_all_bs160_allneg_finetuned_webnlg2020_correctness_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bislama_all_bs160_allneg_finetuned_webnlg2020_correctness_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.3 MB|
+
+## References
+
+https://huggingface.co/teven/bi_all_bs160_allneg_finetuned_WebNLG2020_correctness
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-bsc_bio_ehr_spanish_cantemist_ner_en.md b/docs/_posts/ahmedlone127/2024-09-07-bsc_bio_ehr_spanish_cantemist_ner_en.md
new file mode 100644
index 00000000000000..cd959e2b970542
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-bsc_bio_ehr_spanish_cantemist_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bsc_bio_ehr_spanish_cantemist_ner RoBertaForTokenClassification from Rodrigo1771
+author: John Snow Labs
+name: bsc_bio_ehr_spanish_cantemist_ner
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bsc_bio_ehr_spanish_cantemist_ner` is a English model originally trained by Rodrigo1771.
+
+{:.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/bsc_bio_ehr_spanish_cantemist_ner_en_5.5.0_3.0_1725707974140.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_cantemist_ner_en_5.5.0_3.0_1725707974140.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("bsc_bio_ehr_spanish_cantemist_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("bsc_bio_ehr_spanish_cantemist_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bsc_bio_ehr_spanish_cantemist_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|437.2 MB|
+
+## References
+
+https://huggingface.co/Rodrigo1771/bsc-bio-ehr-es-cantemist-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-bsc_bio_ehr_spanish_combined_train_drugtemist_dev_ner_en.md b/docs/_posts/ahmedlone127/2024-09-07-bsc_bio_ehr_spanish_combined_train_drugtemist_dev_ner_en.md
new file mode 100644
index 00000000000000..60cb35c65dbb3d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-bsc_bio_ehr_spanish_combined_train_drugtemist_dev_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bsc_bio_ehr_spanish_combined_train_drugtemist_dev_ner RoBertaForTokenClassification from Rodrigo1771
+author: John Snow Labs
+name: bsc_bio_ehr_spanish_combined_train_drugtemist_dev_ner
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bsc_bio_ehr_spanish_combined_train_drugtemist_dev_ner` is a English model originally trained by Rodrigo1771.
+
+{:.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/bsc_bio_ehr_spanish_combined_train_drugtemist_dev_ner_en_5.5.0_3.0_1725668584927.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_combined_train_drugtemist_dev_ner_en_5.5.0_3.0_1725668584927.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("bsc_bio_ehr_spanish_combined_train_drugtemist_dev_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("bsc_bio_ehr_spanish_combined_train_drugtemist_dev_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bsc_bio_ehr_spanish_combined_train_drugtemist_dev_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|440.5 MB|
+
+## References
+
+https://huggingface.co/Rodrigo1771/bsc-bio-ehr-es-combined-train-drugtemist-dev-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-bsc_bio_ehr_spanish_symptemist_ner_en.md b/docs/_posts/ahmedlone127/2024-09-07-bsc_bio_ehr_spanish_symptemist_ner_en.md
new file mode 100644
index 00000000000000..d71ae47d0078ce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-bsc_bio_ehr_spanish_symptemist_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bsc_bio_ehr_spanish_symptemist_ner RoBertaForTokenClassification from Rodrigo1771
+author: John Snow Labs
+name: bsc_bio_ehr_spanish_symptemist_ner
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bsc_bio_ehr_spanish_symptemist_ner` is a English model originally trained by Rodrigo1771.
+
+{:.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/bsc_bio_ehr_spanish_symptemist_ner_en_5.5.0_3.0_1725668454204.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_symptemist_ner_en_5.5.0_3.0_1725668454204.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("bsc_bio_ehr_spanish_symptemist_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("bsc_bio_ehr_spanish_symptemist_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bsc_bio_ehr_spanish_symptemist_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|434.9 MB|
+
+## References
+
+https://huggingface.co/Rodrigo1771/bsc-bio-ehr-es-symptemist-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_distil_huner_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_distil_huner_model_pipeline_en.md
new file mode 100644
index 00000000000000..c8d4fc51419cad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_distil_huner_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_distil_huner_model_pipeline pipeline DistilBertForTokenClassification from Balu94pratap
+author: John Snow Labs
+name: burmese_awesome_distil_huner_model_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_distil_huner_model_pipeline` is a English model originally trained by Balu94pratap.
+
+{:.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/burmese_awesome_distil_huner_model_pipeline_en_5.5.0_3.0_1725731029665.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_distil_huner_model_pipeline_en_5.5.0_3.0_1725731029665.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
+
+pipeline = PretrainedPipeline("burmese_awesome_distil_huner_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_distil_huner_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_distil_huner_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Balu94pratap/my_awesome_distil_huner_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_model_mohsinshah_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_model_mohsinshah_pipeline_en.md
new file mode 100644
index 00000000000000..5c8e8feaf21f41
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_model_mohsinshah_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_mohsinshah_pipeline pipeline DistilBertForSequenceClassification from mohsinshah
+author: John Snow Labs
+name: burmese_awesome_model_mohsinshah_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_mohsinshah_pipeline` is a English model originally trained by mohsinshah.
+
+{:.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/burmese_awesome_model_mohsinshah_pipeline_en_5.5.0_3.0_1725675130394.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_mohsinshah_pipeline_en_5.5.0_3.0_1725675130394.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
+
+pipeline = PretrainedPipeline("burmese_awesome_model_mohsinshah_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_mohsinshah_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_mohsinshah_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/mohsinshah/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model3_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model3_en.md
new file mode 100644
index 00000000000000..b78587ed5e4036
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model3_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model3 DistilBertForQuestionAnswering from jvasdigital
+author: John Snow Labs
+name: burmese_awesome_qa_model3
+date: 2024-09-07
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model3` is a English model originally trained by jvasdigital.
+
+{:.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/burmese_awesome_qa_model3_en_5.5.0_3.0_1725736354118.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model3_en_5.5.0_3.0_1725736354118.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model3","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model3", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/jvasdigital/my_awesome_qa_model3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_anoreen_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_anoreen_en.md
new file mode 100644
index 00000000000000..e9866848854fb7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_anoreen_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_anoreen DistilBertForQuestionAnswering from anoreen
+author: John Snow Labs
+name: burmese_awesome_qa_model_anoreen
+date: 2024-09-07
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_anoreen` is a English model originally trained by anoreen.
+
+{:.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/burmese_awesome_qa_model_anoreen_en_5.5.0_3.0_1725722802676.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_anoreen_en_5.5.0_3.0_1725722802676.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_anoreen","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_anoreen", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_anoreen|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/anoreen/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_anoreen_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_anoreen_pipeline_en.md
new file mode 100644
index 00000000000000..b24476758feb39
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_anoreen_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_anoreen_pipeline pipeline DistilBertForQuestionAnswering from anoreen
+author: John Snow Labs
+name: burmese_awesome_qa_model_anoreen_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_anoreen_pipeline` is a English model originally trained by anoreen.
+
+{:.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/burmese_awesome_qa_model_anoreen_pipeline_en_5.5.0_3.0_1725722813867.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_anoreen_pipeline_en_5.5.0_3.0_1725722813867.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_anoreen_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_anoreen_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_anoreen_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/anoreen/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_asier86_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_asier86_pipeline_en.md
new file mode 100644
index 00000000000000..5c88b1f6b75873
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_asier86_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_asier86_pipeline pipeline DistilBertForQuestionAnswering from asier86
+author: John Snow Labs
+name: burmese_awesome_qa_model_asier86_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_asier86_pipeline` is a English model originally trained by asier86.
+
+{:.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/burmese_awesome_qa_model_asier86_pipeline_en_5.5.0_3.0_1725735876211.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_asier86_pipeline_en_5.5.0_3.0_1725735876211.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_asier86_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_asier86_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_asier86_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/asier86/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_ayushij074_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_ayushij074_en.md
new file mode 100644
index 00000000000000..f3c485494234a8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_ayushij074_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_ayushij074 DistilBertForQuestionAnswering from Ayushij074
+author: John Snow Labs
+name: burmese_awesome_qa_model_ayushij074
+date: 2024-09-07
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_ayushij074` is a English model originally trained by Ayushij074.
+
+{:.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/burmese_awesome_qa_model_ayushij074_en_5.5.0_3.0_1725745810555.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_ayushij074_en_5.5.0_3.0_1725745810555.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_ayushij074","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_ayushij074", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_ayushij074|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Ayushij074/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_d29_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_d29_pipeline_en.md
new file mode 100644
index 00000000000000..9a173722f6df1e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_d29_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_d29_pipeline pipeline DistilBertForQuestionAnswering from D29
+author: John Snow Labs
+name: burmese_awesome_qa_model_d29_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_d29_pipeline` is a English model originally trained by D29.
+
+{:.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/burmese_awesome_qa_model_d29_pipeline_en_5.5.0_3.0_1725722320395.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_d29_pipeline_en_5.5.0_3.0_1725722320395.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_d29_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_d29_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_d29_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/D29/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_dldnlee_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_dldnlee_en.md
new file mode 100644
index 00000000000000..b0bcc8e8658ef4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_dldnlee_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_dldnlee DistilBertForQuestionAnswering from dldnlee
+author: John Snow Labs
+name: burmese_awesome_qa_model_dldnlee
+date: 2024-09-07
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_dldnlee` is a English model originally trained by dldnlee.
+
+{:.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/burmese_awesome_qa_model_dldnlee_en_5.5.0_3.0_1725736096527.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_dldnlee_en_5.5.0_3.0_1725736096527.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_dldnlee","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_dldnlee", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_dldnlee|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/dldnlee/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_dldnlee_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_dldnlee_pipeline_en.md
new file mode 100644
index 00000000000000..0803e5479b470f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_dldnlee_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_dldnlee_pipeline pipeline DistilBertForQuestionAnswering from dldnlee
+author: John Snow Labs
+name: burmese_awesome_qa_model_dldnlee_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_dldnlee_pipeline` is a English model originally trained by dldnlee.
+
+{:.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/burmese_awesome_qa_model_dldnlee_pipeline_en_5.5.0_3.0_1725736108928.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_dldnlee_pipeline_en_5.5.0_3.0_1725736108928.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_dldnlee_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_dldnlee_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_dldnlee_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/dldnlee/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_gaogao8_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_gaogao8_en.md
new file mode 100644
index 00000000000000..14107ff9ec27ec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_gaogao8_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_gaogao8 DistilBertForQuestionAnswering from gaogao8
+author: John Snow Labs
+name: burmese_awesome_qa_model_gaogao8
+date: 2024-09-07
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_gaogao8` is a English model originally trained by gaogao8.
+
+{:.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/burmese_awesome_qa_model_gaogao8_en_5.5.0_3.0_1725746163274.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_gaogao8_en_5.5.0_3.0_1725746163274.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_gaogao8","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_gaogao8", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_gaogao8|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/gaogao8/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_gekyume_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_gekyume_en.md
new file mode 100644
index 00000000000000..a525672ec362fa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_gekyume_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_gekyume DistilBertForQuestionAnswering from Gekyume
+author: John Snow Labs
+name: burmese_awesome_qa_model_gekyume
+date: 2024-09-07
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_gekyume` is a English model originally trained by Gekyume.
+
+{:.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/burmese_awesome_qa_model_gekyume_en_5.5.0_3.0_1725746253274.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_gekyume_en_5.5.0_3.0_1725746253274.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_gekyume","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_gekyume", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_gekyume|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Gekyume/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_jafs1986_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_jafs1986_pipeline_en.md
new file mode 100644
index 00000000000000..88c86c0a39177c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_jafs1986_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_jafs1986_pipeline pipeline DistilBertForQuestionAnswering from jafs1986
+author: John Snow Labs
+name: burmese_awesome_qa_model_jafs1986_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_jafs1986_pipeline` is a English model originally trained by jafs1986.
+
+{:.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/burmese_awesome_qa_model_jafs1986_pipeline_en_5.5.0_3.0_1725722429439.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_jafs1986_pipeline_en_5.5.0_3.0_1725722429439.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_jafs1986_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_jafs1986_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_jafs1986_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/jafs1986/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_jyl480_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_jyl480_pipeline_en.md
new file mode 100644
index 00000000000000..c0c2d48a66ed49
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_jyl480_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_jyl480_pipeline pipeline DistilBertForQuestionAnswering from JYL480
+author: John Snow Labs
+name: burmese_awesome_qa_model_jyl480_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_jyl480_pipeline` is a English model originally trained by JYL480.
+
+{:.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/burmese_awesome_qa_model_jyl480_pipeline_en_5.5.0_3.0_1725746043503.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_jyl480_pipeline_en_5.5.0_3.0_1725746043503.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_jyl480_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_jyl480_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_jyl480_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/JYL480/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_kalyanmaram_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_kalyanmaram_en.md
new file mode 100644
index 00000000000000..58272993a294a9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_kalyanmaram_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_kalyanmaram DistilBertForQuestionAnswering from kalyanmaram
+author: John Snow Labs
+name: burmese_awesome_qa_model_kalyanmaram
+date: 2024-09-07
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_kalyanmaram` is a English model originally trained by kalyanmaram.
+
+{:.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/burmese_awesome_qa_model_kalyanmaram_en_5.5.0_3.0_1725695167057.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_kalyanmaram_en_5.5.0_3.0_1725695167057.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_kalyanmaram","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_kalyanmaram", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_kalyanmaram|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/kalyanmaram/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_khadidja22_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_khadidja22_en.md
new file mode 100644
index 00000000000000..c74fde8c177926
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_khadidja22_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_khadidja22 DistilBertForQuestionAnswering from Khadidja22
+author: John Snow Labs
+name: burmese_awesome_qa_model_khadidja22
+date: 2024-09-07
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_khadidja22` is a English model originally trained by Khadidja22.
+
+{:.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/burmese_awesome_qa_model_khadidja22_en_5.5.0_3.0_1725727311967.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_khadidja22_en_5.5.0_3.0_1725727311967.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_khadidja22","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_khadidja22", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_khadidja22|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Khadidja22/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_krayray_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_krayray_pipeline_en.md
new file mode 100644
index 00000000000000..49a149c40c5d4a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_krayray_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_krayray_pipeline pipeline DistilBertForQuestionAnswering from KRayRay
+author: John Snow Labs
+name: burmese_awesome_qa_model_krayray_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_krayray_pipeline` is a English model originally trained by KRayRay.
+
+{:.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/burmese_awesome_qa_model_krayray_pipeline_en_5.5.0_3.0_1725695353067.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_krayray_pipeline_en_5.5.0_3.0_1725695353067.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_krayray_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_krayray_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_krayray_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/KRayRay/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_leytonc_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_leytonc_en.md
new file mode 100644
index 00000000000000..08079b9e8e353e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_leytonc_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_leytonc DistilBertForQuestionAnswering from LeytonC
+author: John Snow Labs
+name: burmese_awesome_qa_model_leytonc
+date: 2024-09-07
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_leytonc` is a English model originally trained by LeytonC.
+
+{:.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/burmese_awesome_qa_model_leytonc_en_5.5.0_3.0_1725735676272.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_leytonc_en_5.5.0_3.0_1725735676272.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_leytonc","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_leytonc", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_leytonc|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/LeytonC/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_mcuallen_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_mcuallen_pipeline_en.md
new file mode 100644
index 00000000000000..0a1db020f10467
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_mcuallen_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_mcuallen_pipeline pipeline DistilBertForQuestionAnswering from mcuallen
+author: John Snow Labs
+name: burmese_awesome_qa_model_mcuallen_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_mcuallen_pipeline` is a English model originally trained by mcuallen.
+
+{:.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/burmese_awesome_qa_model_mcuallen_pipeline_en_5.5.0_3.0_1725735856082.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_mcuallen_pipeline_en_5.5.0_3.0_1725735856082.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_mcuallen_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_mcuallen_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_mcuallen_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/mcuallen/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_nadidebeyza_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_nadidebeyza_pipeline_en.md
new file mode 100644
index 00000000000000..efe4c78802026b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_nadidebeyza_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_nadidebeyza_pipeline pipeline DistilBertForQuestionAnswering from nadidebeyza
+author: John Snow Labs
+name: burmese_awesome_qa_model_nadidebeyza_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_nadidebeyza_pipeline` is a English model originally trained by nadidebeyza.
+
+{:.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/burmese_awesome_qa_model_nadidebeyza_pipeline_en_5.5.0_3.0_1725722890763.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_nadidebeyza_pipeline_en_5.5.0_3.0_1725722890763.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_nadidebeyza_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_nadidebeyza_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_nadidebeyza_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/nadidebeyza/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_pavi156_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_pavi156_en.md
new file mode 100644
index 00000000000000..7ec2ca0315f526
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_pavi156_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_pavi156 DistilBertForQuestionAnswering from pavi156
+author: John Snow Labs
+name: burmese_awesome_qa_model_pavi156
+date: 2024-09-07
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_pavi156` is a English model originally trained by pavi156.
+
+{:.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/burmese_awesome_qa_model_pavi156_en_5.5.0_3.0_1725736338269.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_pavi156_en_5.5.0_3.0_1725736338269.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_pavi156","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_pavi156", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_pavi156|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/pavi156/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_venkatarajendra_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_venkatarajendra_pipeline_en.md
new file mode 100644
index 00000000000000..7e06b8a147081e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_venkatarajendra_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_venkatarajendra_pipeline pipeline DistilBertForQuestionAnswering from venkatarajendra
+author: John Snow Labs
+name: burmese_awesome_qa_model_venkatarajendra_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_venkatarajendra_pipeline` is a English model originally trained by venkatarajendra.
+
+{:.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/burmese_awesome_qa_model_venkatarajendra_pipeline_en_5.5.0_3.0_1725727002710.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_venkatarajendra_pipeline_en_5.5.0_3.0_1725727002710.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_venkatarajendra_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_venkatarajendra_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_venkatarajendra_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/venkatarajendra/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_wandaabudiono_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_wandaabudiono_pipeline_en.md
new file mode 100644
index 00000000000000..ccbf0cc64ece9b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_wandaabudiono_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_wandaabudiono_pipeline pipeline DistilBertForQuestionAnswering from WandaaBudiono
+author: John Snow Labs
+name: burmese_awesome_qa_model_wandaabudiono_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_wandaabudiono_pipeline` is a English model originally trained by WandaaBudiono.
+
+{:.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/burmese_awesome_qa_model_wandaabudiono_pipeline_en_5.5.0_3.0_1725745637391.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_wandaabudiono_pipeline_en_5.5.0_3.0_1725745637391.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_wandaabudiono_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_wandaabudiono_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_wandaabudiono_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/WandaaBudiono/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_wyxwangmed_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_wyxwangmed_en.md
new file mode 100644
index 00000000000000..f565ddf6380d09
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_wyxwangmed_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_wyxwangmed DistilBertForQuestionAnswering from wyxwangmed
+author: John Snow Labs
+name: burmese_awesome_qa_model_wyxwangmed
+date: 2024-09-07
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_wyxwangmed` is a English model originally trained by wyxwangmed.
+
+{:.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/burmese_awesome_qa_model_wyxwangmed_en_5.5.0_3.0_1725722942544.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_wyxwangmed_en_5.5.0_3.0_1725722942544.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_wyxwangmed","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_wyxwangmed", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_wyxwangmed|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/wyxwangmed/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_wyxwangmed_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_wyxwangmed_pipeline_en.md
new file mode 100644
index 00000000000000..8346c8669c546f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_qa_model_wyxwangmed_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_wyxwangmed_pipeline pipeline DistilBertForQuestionAnswering from wyxwangmed
+author: John Snow Labs
+name: burmese_awesome_qa_model_wyxwangmed_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_wyxwangmed_pipeline` is a English model originally trained by wyxwangmed.
+
+{:.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/burmese_awesome_qa_model_wyxwangmed_pipeline_en_5.5.0_3.0_1725722954243.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_wyxwangmed_pipeline_en_5.5.0_3.0_1725722954243.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_wyxwangmed_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_wyxwangmed_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_wyxwangmed_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/wyxwangmed/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_setfit_model_ivanzidov_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_setfit_model_ivanzidov_pipeline_en.md
new file mode 100644
index 00000000000000..ce153994f5db95
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_setfit_model_ivanzidov_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_setfit_model_ivanzidov_pipeline pipeline MPNetEmbeddings from ivanzidov
+author: John Snow Labs
+name: burmese_awesome_setfit_model_ivanzidov_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_setfit_model_ivanzidov_pipeline` is a English model originally trained by ivanzidov.
+
+{:.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/burmese_awesome_setfit_model_ivanzidov_pipeline_en_5.5.0_3.0_1725703151255.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_ivanzidov_pipeline_en_5.5.0_3.0_1725703151255.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
+
+pipeline = PretrainedPipeline("burmese_awesome_setfit_model_ivanzidov_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_setfit_model_ivanzidov_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_setfit_model_ivanzidov_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/ivanzidov/my-awesome-setfit-model
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_all_jhs_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_all_jhs_en.md
new file mode 100644
index 00000000000000..ce356a985d8741
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_all_jhs_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_all_jhs DistilBertForTokenClassification from gonzalezrostani
+author: John Snow Labs
+name: burmese_awesome_wnut_all_jhs
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_all_jhs` is a English model originally trained by gonzalezrostani.
+
+{:.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/burmese_awesome_wnut_all_jhs_en_5.5.0_3.0_1725739475984.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_all_jhs_en_5.5.0_3.0_1725739475984.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_all_jhs","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_all_jhs", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_all_jhs|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/gonzalezrostani/my_awesome_wnut_all_JHs
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_all_place_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_all_place_pipeline_en.md
new file mode 100644
index 00000000000000..3c9a045cf3fe85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_all_place_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_all_place_pipeline pipeline DistilBertForTokenClassification from gonzalezrostani
+author: John Snow Labs
+name: burmese_awesome_wnut_all_place_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_all_place_pipeline` is a English model originally trained by gonzalezrostani.
+
+{:.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/burmese_awesome_wnut_all_place_pipeline_en_5.5.0_3.0_1725739288960.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_all_place_pipeline_en_5.5.0_3.0_1725739288960.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
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_all_place_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_all_place_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_all_place_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/gonzalezrostani/my_awesome_wnut_all_Place
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_jgtg_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_jgtg_pipeline_en.md
new file mode 100644
index 00000000000000..1db10d64ca0163
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_jgtg_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_jgtg_pipeline pipeline DistilBertForTokenClassification from gonzalezrostani
+author: John Snow Labs
+name: burmese_awesome_wnut_jgtg_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_jgtg_pipeline` is a English model originally trained by gonzalezrostani.
+
+{:.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/burmese_awesome_wnut_jgtg_pipeline_en_5.5.0_3.0_1725730249248.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_jgtg_pipeline_en_5.5.0_3.0_1725730249248.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
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_jgtg_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_jgtg_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_jgtg_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/gonzalezrostani/my_awesome_wnut_JGTg
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_model_anirudhramoo_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_model_anirudhramoo_pipeline_en.md
new file mode 100644
index 00000000000000..6b40ba5daa117f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_model_anirudhramoo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_anirudhramoo_pipeline pipeline DistilBertForTokenClassification from anirudhramoo
+author: John Snow Labs
+name: burmese_awesome_wnut_model_anirudhramoo_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_anirudhramoo_pipeline` is a English model originally trained by anirudhramoo.
+
+{:.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/burmese_awesome_wnut_model_anirudhramoo_pipeline_en_5.5.0_3.0_1725739232189.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_anirudhramoo_pipeline_en_5.5.0_3.0_1725739232189.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
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_anirudhramoo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_anirudhramoo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_anirudhramoo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/anirudhramoo/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_model_dkababgi_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_model_dkababgi_en.md
new file mode 100644
index 00000000000000..7c42e2b32a8fcb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_model_dkababgi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_dkababgi DistilBertForTokenClassification from dkababgi
+author: John Snow Labs
+name: burmese_awesome_wnut_model_dkababgi
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_dkababgi` is a English model originally trained by dkababgi.
+
+{:.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/burmese_awesome_wnut_model_dkababgi_en_5.5.0_3.0_1725730152637.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_dkababgi_en_5.5.0_3.0_1725730152637.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_dkababgi","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_dkababgi", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_dkababgi|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/dkababgi/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_model_joshcarp_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_model_joshcarp_en.md
new file mode 100644
index 00000000000000..808c9347b0e812
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_model_joshcarp_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_joshcarp DistilBertForTokenClassification from joshcarp
+author: John Snow Labs
+name: burmese_awesome_wnut_model_joshcarp
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_joshcarp` is a English model originally trained by joshcarp.
+
+{:.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/burmese_awesome_wnut_model_joshcarp_en_5.5.0_3.0_1725729771291.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_joshcarp_en_5.5.0_3.0_1725729771291.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_joshcarp","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_joshcarp", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_joshcarp|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/joshcarp/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_model_mandasrinu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_model_mandasrinu_pipeline_en.md
new file mode 100644
index 00000000000000..df0e99df50b658
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_model_mandasrinu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_mandasrinu_pipeline pipeline DistilBertForTokenClassification from mandasrinu
+author: John Snow Labs
+name: burmese_awesome_wnut_model_mandasrinu_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_mandasrinu_pipeline` is a English model originally trained by mandasrinu.
+
+{:.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/burmese_awesome_wnut_model_mandasrinu_pipeline_en_5.5.0_3.0_1725730361176.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_mandasrinu_pipeline_en_5.5.0_3.0_1725730361176.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
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_mandasrinu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_mandasrinu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_mandasrinu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/mandasrinu/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_model_navnitan_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_model_navnitan_pipeline_en.md
new file mode 100644
index 00000000000000..aa37d3c32500c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_model_navnitan_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_navnitan_pipeline pipeline DistilBertForTokenClassification from navnitan
+author: John Snow Labs
+name: burmese_awesome_wnut_model_navnitan_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_navnitan_pipeline` is a English model originally trained by navnitan.
+
+{:.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/burmese_awesome_wnut_model_navnitan_pipeline_en_5.5.0_3.0_1725729703003.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_navnitan_pipeline_en_5.5.0_3.0_1725729703003.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
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_navnitan_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_navnitan_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_navnitan_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/navnitan/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_model_paulbin_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_model_paulbin_pipeline_en.md
new file mode 100644
index 00000000000000..8d477a5994b278
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_model_paulbin_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_paulbin_pipeline pipeline DistilBertForTokenClassification from PaulBin
+author: John Snow Labs
+name: burmese_awesome_wnut_model_paulbin_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_paulbin_pipeline` is a English model originally trained by PaulBin.
+
+{:.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/burmese_awesome_wnut_model_paulbin_pipeline_en_5.5.0_3.0_1725729677086.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_paulbin_pipeline_en_5.5.0_3.0_1725729677086.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
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_paulbin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_paulbin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_paulbin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/PaulBin/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_model_priyanshug0405_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_model_priyanshug0405_en.md
new file mode 100644
index 00000000000000..d70ed5e3cadfe1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_model_priyanshug0405_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_priyanshug0405 DistilBertForTokenClassification from priyanshug0405
+author: John Snow Labs
+name: burmese_awesome_wnut_model_priyanshug0405
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_priyanshug0405` is a English model originally trained by priyanshug0405.
+
+{:.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/burmese_awesome_wnut_model_priyanshug0405_en_5.5.0_3.0_1725739116274.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_priyanshug0405_en_5.5.0_3.0_1725739116274.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_priyanshug0405","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_priyanshug0405", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_priyanshug0405|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/priyanshug0405/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_model_wstcpyt1988_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_model_wstcpyt1988_pipeline_en.md
new file mode 100644
index 00000000000000..9647d570fcded3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_awesome_wnut_model_wstcpyt1988_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_wstcpyt1988_pipeline pipeline DistilBertForTokenClassification from wstcpyt1988
+author: John Snow Labs
+name: burmese_awesome_wnut_model_wstcpyt1988_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_wstcpyt1988_pipeline` is a English model originally trained by wstcpyt1988.
+
+{:.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/burmese_awesome_wnut_model_wstcpyt1988_pipeline_en_5.5.0_3.0_1725739378501.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_wstcpyt1988_pipeline_en_5.5.0_3.0_1725739378501.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
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_wstcpyt1988_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_wstcpyt1988_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_wstcpyt1988_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/wstcpyt1988/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_distilbert_model_prasadavidi_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_distilbert_model_prasadavidi_en.md
new file mode 100644
index 00000000000000..f0d6586f3b32dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_distilbert_model_prasadavidi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_distilbert_model_prasadavidi DistilBertForSequenceClassification from PrasadAvidi
+author: John Snow Labs
+name: burmese_distilbert_model_prasadavidi
+date: 2024-09-07
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_distilbert_model_prasadavidi` is a English model originally trained by PrasadAvidi.
+
+{:.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/burmese_distilbert_model_prasadavidi_en_5.5.0_3.0_1725674743036.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_distilbert_model_prasadavidi_en_5.5.0_3.0_1725674743036.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_distilbert_model_prasadavidi","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_distilbert_model_prasadavidi", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_distilbert_model_prasadavidi|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/PrasadAvidi/my_distilbert_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_dummy_model_chase4eck_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_dummy_model_chase4eck_pipeline_en.md
new file mode 100644
index 00000000000000..f9040cd8612f7a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_dummy_model_chase4eck_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_dummy_model_chase4eck_pipeline pipeline CamemBertEmbeddings from chase4eck
+author: John Snow Labs
+name: burmese_dummy_model_chase4eck_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_dummy_model_chase4eck_pipeline` is a English model originally trained by chase4eck.
+
+{:.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/burmese_dummy_model_chase4eck_pipeline_en_5.5.0_3.0_1725728722457.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_dummy_model_chase4eck_pipeline_en_5.5.0_3.0_1725728722457.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
+
+pipeline = PretrainedPipeline("burmese_dummy_model_chase4eck_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_dummy_model_chase4eck_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_dummy_model_chase4eck_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/chase4eck/my-dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_model_rouhan_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_model_rouhan_en.md
new file mode 100644
index 00000000000000..d5da6da32afed7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_model_rouhan_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_model_rouhan DistilBertForQuestionAnswering from Rouhan
+author: John Snow Labs
+name: burmese_model_rouhan
+date: 2024-09-07
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_model_rouhan` is a English model originally trained by Rouhan.
+
+{:.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/burmese_model_rouhan_en_5.5.0_3.0_1725735779350.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_model_rouhan_en_5.5.0_3.0_1725735779350.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_model_rouhan","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_model_rouhan", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_model_rouhan|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Rouhan/my_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_ner_model_veronica1608_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_ner_model_veronica1608_en.md
new file mode 100644
index 00000000000000..5a6b2ba8496303
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_ner_model_veronica1608_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_ner_model_veronica1608 DistilBertForTokenClassification from veronica1608
+author: John Snow Labs
+name: burmese_ner_model_veronica1608
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_ner_model_veronica1608` is a English model originally trained by veronica1608.
+
+{:.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/burmese_ner_model_veronica1608_en_5.5.0_3.0_1725730775380.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_ner_model_veronica1608_en_5.5.0_3.0_1725730775380.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_ner_model_veronica1608","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_ner_model_veronica1608", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_ner_model_veronica1608|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/veronica1608/my_ner_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_nmt_model_antaraiiitd_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_nmt_model_antaraiiitd_pipeline_en.md
new file mode 100644
index 00000000000000..59b0113c0a8cb9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_nmt_model_antaraiiitd_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_nmt_model_antaraiiitd_pipeline pipeline MarianTransformer from AntaraIIITD
+author: John Snow Labs
+name: burmese_nmt_model_antaraiiitd_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_nmt_model_antaraiiitd_pipeline` is a English model originally trained by AntaraIIITD.
+
+{:.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/burmese_nmt_model_antaraiiitd_pipeline_en_5.5.0_3.0_1725747930202.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_nmt_model_antaraiiitd_pipeline_en_5.5.0_3.0_1725747930202.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
+
+pipeline = PretrainedPipeline("burmese_nmt_model_antaraiiitd_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_nmt_model_antaraiiitd_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_nmt_model_antaraiiitd_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|500.7 MB|
+
+## References
+
+https://huggingface.co/AntaraIIITD/my_NMT_model
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_qa_model_arunkarthik_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_qa_model_arunkarthik_en.md
new file mode 100644
index 00000000000000..fa466fc92a9a6e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_qa_model_arunkarthik_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_qa_model_arunkarthik DistilBertForQuestionAnswering from arunkarthik
+author: John Snow Labs
+name: burmese_qa_model_arunkarthik
+date: 2024-09-07
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_qa_model_arunkarthik` is a English model originally trained by arunkarthik.
+
+{:.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/burmese_qa_model_arunkarthik_en_5.5.0_3.0_1725746068903.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_qa_model_arunkarthik_en_5.5.0_3.0_1725746068903.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_qa_model_arunkarthik","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_qa_model_arunkarthik", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_qa_model_arunkarthik|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/arunkarthik/my_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_qa_model_rosa_alvarez_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_qa_model_rosa_alvarez_en.md
new file mode 100644
index 00000000000000..07d4c4da8fd1e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_qa_model_rosa_alvarez_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_qa_model_rosa_alvarez DistilBertForQuestionAnswering from rosa-alvarez
+author: John Snow Labs
+name: burmese_qa_model_rosa_alvarez
+date: 2024-09-07
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_qa_model_rosa_alvarez` is a English model originally trained by rosa-alvarez.
+
+{:.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/burmese_qa_model_rosa_alvarez_en_5.5.0_3.0_1725722995502.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_qa_model_rosa_alvarez_en_5.5.0_3.0_1725722995502.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_qa_model_rosa_alvarez","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_qa_model_rosa_alvarez", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_qa_model_rosa_alvarez|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/rosa-alvarez/my_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_qa_model_rosa_alvarez_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_qa_model_rosa_alvarez_pipeline_en.md
new file mode 100644
index 00000000000000..45a6e83d8aaeb6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_qa_model_rosa_alvarez_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_qa_model_rosa_alvarez_pipeline pipeline DistilBertForQuestionAnswering from rosa-alvarez
+author: John Snow Labs
+name: burmese_qa_model_rosa_alvarez_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_qa_model_rosa_alvarez_pipeline` is a English model originally trained by rosa-alvarez.
+
+{:.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/burmese_qa_model_rosa_alvarez_pipeline_en_5.5.0_3.0_1725723007238.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_qa_model_rosa_alvarez_pipeline_en_5.5.0_3.0_1725723007238.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
+
+pipeline = PretrainedPipeline("burmese_qa_model_rosa_alvarez_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_qa_model_rosa_alvarez_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_qa_model_rosa_alvarez_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/rosa-alvarez/my_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_spanish_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_spanish_model_pipeline_en.md
new file mode 100644
index 00000000000000..5e67848e6a9dc4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_spanish_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_spanish_model_pipeline pipeline DistilBertForQuestionAnswering from jeguinoa
+author: John Snow Labs
+name: burmese_spanish_model_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_spanish_model_pipeline` is a English model originally trained by jeguinoa.
+
+{:.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/burmese_spanish_model_pipeline_en_5.5.0_3.0_1725736147634.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_spanish_model_pipeline_en_5.5.0_3.0_1725736147634.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
+
+pipeline = PretrainedPipeline("burmese_spanish_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_spanish_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_spanish_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|250.2 MB|
+
+## References
+
+https://huggingface.co/jeguinoa/my_spanish_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-burmese_wnut_model_samasedaghat_en.md b/docs/_posts/ahmedlone127/2024-09-07-burmese_wnut_model_samasedaghat_en.md
new file mode 100644
index 00000000000000..5c0fe8ca01c90a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-burmese_wnut_model_samasedaghat_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_wnut_model_samasedaghat DistilBertForTokenClassification from SamaSedaghat
+author: John Snow Labs
+name: burmese_wnut_model_samasedaghat
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_wnut_model_samasedaghat` is a English model originally trained by SamaSedaghat.
+
+{:.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/burmese_wnut_model_samasedaghat_en_5.5.0_3.0_1725739306704.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_wnut_model_samasedaghat_en_5.5.0_3.0_1725739306704.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_wnut_model_samasedaghat","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_wnut_model_samasedaghat", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_wnut_model_samasedaghat|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/SamaSedaghat/my_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-cat_ner_spanish_4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-cat_ner_spanish_4_pipeline_en.md
new file mode 100644
index 00000000000000..da70a2a4a38d53
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-cat_ner_spanish_4_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cat_ner_spanish_4_pipeline pipeline RoBertaForTokenClassification from homersimpson
+author: John Snow Labs
+name: cat_ner_spanish_4_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cat_ner_spanish_4_pipeline` is a English model originally trained by homersimpson.
+
+{:.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/cat_ner_spanish_4_pipeline_en_5.5.0_3.0_1725724144889.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cat_ner_spanish_4_pipeline_en_5.5.0_3.0_1725724144889.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
+
+pipeline = PretrainedPipeline("cat_ner_spanish_4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cat_ner_spanish_4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cat_ner_spanish_4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|462.3 MB|
+
+## References
+
+https://huggingface.co/homersimpson/cat-ner-es-4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-cat_sayula_popoluca_iwcg_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-cat_sayula_popoluca_iwcg_3_pipeline_en.md
new file mode 100644
index 00000000000000..2b6ab427f4f147
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-cat_sayula_popoluca_iwcg_3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cat_sayula_popoluca_iwcg_3_pipeline pipeline XlmRoBertaForTokenClassification from homersimpson
+author: John Snow Labs
+name: cat_sayula_popoluca_iwcg_3_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cat_sayula_popoluca_iwcg_3_pipeline` is a English model originally trained by homersimpson.
+
+{:.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/cat_sayula_popoluca_iwcg_3_pipeline_en_5.5.0_3.0_1725744831176.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cat_sayula_popoluca_iwcg_3_pipeline_en_5.5.0_3.0_1725744831176.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
+
+pipeline = PretrainedPipeline("cat_sayula_popoluca_iwcg_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cat_sayula_popoluca_iwcg_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cat_sayula_popoluca_iwcg_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|432.1 MB|
+
+## References
+
+https://huggingface.co/homersimpson/cat-pos-iwcg-3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-checkingmodel_en.md b/docs/_posts/ahmedlone127/2024-09-07-checkingmodel_en.md
new file mode 100644
index 00000000000000..93ccf1607e8ac5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-checkingmodel_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English checkingmodel DistilBertForTokenClassification from bhadauriaupendra062
+author: John Snow Labs
+name: checkingmodel
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`checkingmodel` is a English model originally trained by bhadauriaupendra062.
+
+{:.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/checkingmodel_en_5.5.0_3.0_1725730838265.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/checkingmodel_en_5.5.0_3.0_1725730838265.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("checkingmodel","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("checkingmodel", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|checkingmodel|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/bhadauriaupendra062/checkingmodel
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-checkingmodel_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-checkingmodel_pipeline_en.md
new file mode 100644
index 00000000000000..26e4617b7941a5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-checkingmodel_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English checkingmodel_pipeline pipeline DistilBertForTokenClassification from bhadauriaupendra062
+author: John Snow Labs
+name: checkingmodel_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`checkingmodel_pipeline` is a English model originally trained by bhadauriaupendra062.
+
+{:.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/checkingmodel_pipeline_en_5.5.0_3.0_1725730850065.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/checkingmodel_pipeline_en_5.5.0_3.0_1725730850065.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
+
+pipeline = PretrainedPipeline("checkingmodel_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("checkingmodel_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|checkingmodel_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/bhadauriaupendra062/checkingmodel
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-clinicalbert_jnlpba_ner_nepal_bhasa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-clinicalbert_jnlpba_ner_nepal_bhasa_pipeline_en.md
new file mode 100644
index 00000000000000..bc7b4341204b58
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-clinicalbert_jnlpba_ner_nepal_bhasa_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English clinicalbert_jnlpba_ner_nepal_bhasa_pipeline pipeline DistilBertForTokenClassification from judithrosell
+author: John Snow Labs
+name: clinicalbert_jnlpba_ner_nepal_bhasa_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clinicalbert_jnlpba_ner_nepal_bhasa_pipeline` is a English model originally trained by judithrosell.
+
+{:.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/clinicalbert_jnlpba_ner_nepal_bhasa_pipeline_en_5.5.0_3.0_1725734198038.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clinicalbert_jnlpba_ner_nepal_bhasa_pipeline_en_5.5.0_3.0_1725734198038.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
+
+pipeline = PretrainedPipeline("clinicalbert_jnlpba_ner_nepal_bhasa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clinicalbert_jnlpba_ner_nepal_bhasa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clinicalbert_jnlpba_ner_nepal_bhasa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/judithrosell/ClinicalBERT_JNLPBA_NER_new
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-coha2000s_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-coha2000s_pipeline_en.md
new file mode 100644
index 00000000000000..4fbe2e97da55d7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-coha2000s_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English coha2000s_pipeline pipeline RoBertaEmbeddings from simonmun
+author: John Snow Labs
+name: coha2000s_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`coha2000s_pipeline` is a English model originally trained by simonmun.
+
+{:.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/coha2000s_pipeline_en_5.5.0_3.0_1725716252588.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/coha2000s_pipeline_en_5.5.0_3.0_1725716252588.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
+
+pipeline = PretrainedPipeline("coha2000s_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("coha2000s_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|coha2000s_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|311.5 MB|
+
+## References
+
+https://huggingface.co/simonmun/COHA2000s
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-cot_ep3_1122_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-cot_ep3_1122_pipeline_en.md
new file mode 100644
index 00000000000000..a4b575d1af2d87
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-cot_ep3_1122_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English cot_ep3_1122_pipeline pipeline MPNetEmbeddings from ingeol
+author: John Snow Labs
+name: cot_ep3_1122_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cot_ep3_1122_pipeline` is a English model originally trained by ingeol.
+
+{:.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/cot_ep3_1122_pipeline_en_5.5.0_3.0_1725703599065.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cot_ep3_1122_pipeline_en_5.5.0_3.0_1725703599065.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
+
+pipeline = PretrainedPipeline("cot_ep3_1122_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cot_ep3_1122_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cot_ep3_1122_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/ingeol/cot_ep3_1122
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-cree_albert_5e_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-cree_albert_5e_pipeline_en.md
new file mode 100644
index 00000000000000..68efc3d1ad0630
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-cree_albert_5e_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cree_albert_5e_pipeline pipeline AlbertForSequenceClassification from pig4431
+author: John Snow Labs
+name: cree_albert_5e_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cree_albert_5e_pipeline` is a English model originally trained by pig4431.
+
+{:.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/cree_albert_5e_pipeline_en_5.5.0_3.0_1725732250740.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cree_albert_5e_pipeline_en_5.5.0_3.0_1725732250740.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
+
+pipeline = PretrainedPipeline("cree_albert_5e_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cree_albert_5e_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cree_albert_5e_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/pig4431/CR_ALBERT_5E
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-cross_encoder_mmarco_mminilmv2_l12_h384_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-cross_encoder_mmarco_mminilmv2_l12_h384_v1_pipeline_en.md
new file mode 100644
index 00000000000000..72ee737e3e42de
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-cross_encoder_mmarco_mminilmv2_l12_h384_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cross_encoder_mmarco_mminilmv2_l12_h384_v1_pipeline pipeline XlmRoBertaForSequenceClassification from corrius
+author: John Snow Labs
+name: cross_encoder_mmarco_mminilmv2_l12_h384_v1_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cross_encoder_mmarco_mminilmv2_l12_h384_v1_pipeline` is a English model originally trained by corrius.
+
+{:.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/cross_encoder_mmarco_mminilmv2_l12_h384_v1_pipeline_en_5.5.0_3.0_1725671130763.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cross_encoder_mmarco_mminilmv2_l12_h384_v1_pipeline_en_5.5.0_3.0_1725671130763.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
+
+pipeline = PretrainedPipeline("cross_encoder_mmarco_mminilmv2_l12_h384_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cross_encoder_mmarco_mminilmv2_l12_h384_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cross_encoder_mmarco_mminilmv2_l12_h384_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|399.6 MB|
+
+## References
+
+https://huggingface.co/corrius/cross-encoder-mmarco-mMiniLMv2-L12-H384-v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-cuad_distil_governing_law_08_25_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-cuad_distil_governing_law_08_25_v1_pipeline_en.md
new file mode 100644
index 00000000000000..1830a54261bb8b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-cuad_distil_governing_law_08_25_v1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English cuad_distil_governing_law_08_25_v1_pipeline pipeline DistilBertForQuestionAnswering from saraks
+author: John Snow Labs
+name: cuad_distil_governing_law_08_25_v1_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cuad_distil_governing_law_08_25_v1_pipeline` is a English model originally trained by saraks.
+
+{:.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/cuad_distil_governing_law_08_25_v1_pipeline_en_5.5.0_3.0_1725722853762.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cuad_distil_governing_law_08_25_v1_pipeline_en_5.5.0_3.0_1725722853762.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
+
+pipeline = PretrainedPipeline("cuad_distil_governing_law_08_25_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cuad_distil_governing_law_08_25_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cuad_distil_governing_law_08_25_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/saraks/cuad-distil-governing_law-08-25-v1
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-cuad_distil_governing_law_08_28_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-cuad_distil_governing_law_08_28_v1_pipeline_en.md
new file mode 100644
index 00000000000000..e04c20c93c0313
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-cuad_distil_governing_law_08_28_v1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English cuad_distil_governing_law_08_28_v1_pipeline pipeline DistilBertForQuestionAnswering from saraks
+author: John Snow Labs
+name: cuad_distil_governing_law_08_28_v1_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cuad_distil_governing_law_08_28_v1_pipeline` is a English model originally trained by saraks.
+
+{:.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/cuad_distil_governing_law_08_28_v1_pipeline_en_5.5.0_3.0_1725727353086.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cuad_distil_governing_law_08_28_v1_pipeline_en_5.5.0_3.0_1725727353086.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
+
+pipeline = PretrainedPipeline("cuad_distil_governing_law_08_28_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cuad_distil_governing_law_08_28_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cuad_distil_governing_law_08_28_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/saraks/cuad-distil-governing_law-08-28-v1
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-cybert_cyner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-cybert_cyner_pipeline_en.md
new file mode 100644
index 00000000000000..15690e855a8e77
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-cybert_cyner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English cybert_cyner_pipeline pipeline RoBertaForTokenClassification from Cyber-ThreaD
+author: John Snow Labs
+name: cybert_cyner_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cybert_cyner_pipeline` is a English model originally trained by Cyber-ThreaD.
+
+{:.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/cybert_cyner_pipeline_en_5.5.0_3.0_1725668553389.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cybert_cyner_pipeline_en_5.5.0_3.0_1725668553389.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
+
+pipeline = PretrainedPipeline("cybert_cyner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cybert_cyner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cybert_cyner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|311.3 MB|
+
+## References
+
+https://huggingface.co/Cyber-ThreaD/CyBERT-CyNER
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-dbbuc_10p_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-dbbuc_10p_pipeline_en.md
new file mode 100644
index 00000000000000..145bef9b856b92
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-dbbuc_10p_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dbbuc_10p_pipeline pipeline DistilBertForTokenClassification from gabizh
+author: John Snow Labs
+name: dbbuc_10p_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dbbuc_10p_pipeline` is a English model originally trained by gabizh.
+
+{:.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/dbbuc_10p_pipeline_en_5.5.0_3.0_1725729989642.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dbbuc_10p_pipeline_en_5.5.0_3.0_1725729989642.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
+
+pipeline = PretrainedPipeline("dbbuc_10p_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dbbuc_10p_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dbbuc_10p_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/gabizh/dbbuc_10p
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-dbert_model_04_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-dbert_model_04_pipeline_en.md
new file mode 100644
index 00000000000000..ce4d653147fe77
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-dbert_model_04_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dbert_model_04_pipeline pipeline DistilBertForTokenClassification from fcfrank10
+author: John Snow Labs
+name: dbert_model_04_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dbert_model_04_pipeline` is a English model originally trained by fcfrank10.
+
+{:.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/dbert_model_04_pipeline_en_5.5.0_3.0_1725739624376.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dbert_model_04_pipeline_en_5.5.0_3.0_1725739624376.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
+
+pipeline = PretrainedPipeline("dbert_model_04_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dbert_model_04_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dbert_model_04_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/fcfrank10/dbert_model_04
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-dicstilbert_finetuned_oppo_en.md b/docs/_posts/ahmedlone127/2024-09-07-dicstilbert_finetuned_oppo_en.md
new file mode 100644
index 00000000000000..07818fa27e9fe8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-dicstilbert_finetuned_oppo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dicstilbert_finetuned_oppo DistilBertForTokenClassification from dtorber
+author: John Snow Labs
+name: dicstilbert_finetuned_oppo
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dicstilbert_finetuned_oppo` is a English model originally trained by dtorber.
+
+{:.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/dicstilbert_finetuned_oppo_en_5.5.0_3.0_1725730974985.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dicstilbert_finetuned_oppo_en_5.5.0_3.0_1725730974985.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("dicstilbert_finetuned_oppo","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("dicstilbert_finetuned_oppo", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dicstilbert_finetuned_oppo|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/dtorber/dicstilbert-finetuned-oppo
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-disaster_tweet_distilbert_en.md b/docs/_posts/ahmedlone127/2024-09-07-disaster_tweet_distilbert_en.md
new file mode 100644
index 00000000000000..89891a90d82ac5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-disaster_tweet_distilbert_en.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: English disaster_tweet_distilbert DistilBertForSequenceClassification from aellxx
+author: John Snow Labs
+name: disaster_tweet_distilbert
+date: 2024-09-07
+tags: [bert, en, open_source, sequence_classification, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`disaster_tweet_distilbert` is a English model originally trained by aellxx.
+
+## 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/disaster_tweet_distilbert_en_5.5.0_3.0_1725674858595.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/disaster_tweet_distilbert_en_5.5.0_3.0_1725674858595.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("document")
+
+tokenizer = Tokenizer()\
+    .setInputCols("document")\
+    .setOutputCol("token")  
+    
+sequenceClassifier = DistilBertForSequenceClassification.pretrained("disaster_tweet_distilbert","en")\
+            .setInputCols(["document","token"])\
+            .setOutputCol("class")
+
+pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text")
+    .setOutputCol("document")
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document") 
+    .setOutputCol("token")  
+    
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("disaster_tweet_distilbert","en")
+            .setInputCols(Array("document","token"))
+            .setOutputCol("class")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|disaster_tweet_distilbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+References
+
+https://huggingface.co/aellxx/disaster-tweet-distilbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-disaster_tweet_distilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-disaster_tweet_distilbert_pipeline_en.md
new file mode 100644
index 00000000000000..d4f19081f12622
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-disaster_tweet_distilbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English disaster_tweet_distilbert_pipeline pipeline DistilBertForSequenceClassification from HilariusJeremy
+author: John Snow Labs
+name: disaster_tweet_distilbert_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`disaster_tweet_distilbert_pipeline` is a English model originally trained by HilariusJeremy.
+
+{:.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/disaster_tweet_distilbert_pipeline_en_5.5.0_3.0_1725674871021.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/disaster_tweet_distilbert_pipeline_en_5.5.0_3.0_1725674871021.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
+
+pipeline = PretrainedPipeline("disaster_tweet_distilbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("disaster_tweet_distilbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|disaster_tweet_distilbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/HilariusJeremy/disaster_tweet_distilbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_cased_finetuned_pfe_projectt_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_cased_finetuned_pfe_projectt_pipeline_en.md
new file mode 100644
index 00000000000000..4d60d91074bc78
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_cased_finetuned_pfe_projectt_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_cased_finetuned_pfe_projectt_pipeline pipeline DistilBertForQuestionAnswering from onsba
+author: John Snow Labs
+name: distilbert_base_cased_finetuned_pfe_projectt_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_cased_finetuned_pfe_projectt_pipeline` is a English model originally trained by onsba.
+
+{:.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/distilbert_base_cased_finetuned_pfe_projectt_pipeline_en_5.5.0_3.0_1725727241771.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_cased_finetuned_pfe_projectt_pipeline_en_5.5.0_3.0_1725727241771.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
+
+pipeline = PretrainedPipeline("distilbert_base_cased_finetuned_pfe_projectt_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_cased_finetuned_pfe_projectt_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_cased_finetuned_pfe_projectt_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/onsba/distilbert-base-cased-finetuned-pfe-projectt
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_turkish_cased_qa_tr.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_turkish_cased_qa_tr.md
new file mode 100644
index 00000000000000..dd7a38b848ef42
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_turkish_cased_qa_tr.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Turkish distilbert_base_turkish_cased_qa DistilBertForQuestionAnswering from incidelen
+author: John Snow Labs
+name: distilbert_base_turkish_cased_qa
+date: 2024-09-07
+tags: [tr, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: tr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_turkish_cased_qa` is a Turkish model originally trained by incidelen.
+
+{:.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/distilbert_base_turkish_cased_qa_tr_5.5.0_3.0_1725722308017.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_turkish_cased_qa_tr_5.5.0_3.0_1725722308017.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_turkish_cased_qa","tr") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_turkish_cased_qa", "tr")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_turkish_cased_qa|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|tr|
+|Size:|251.9 MB|
+
+## References
+
+https://huggingface.co/incidelen/distilbert-base-turkish-cased-qa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_bhavesh1609_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_bhavesh1609_pipeline_en.md
new file mode 100644
index 00000000000000..a3445a45ded4b8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_bhavesh1609_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_bhavesh1609_pipeline pipeline DistilBertForTokenClassification from Bhavesh1609
+author: John Snow Labs
+name: distilbert_base_uncased_bhavesh1609_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_bhavesh1609_pipeline` is a English model originally trained by Bhavesh1609.
+
+{:.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/distilbert_base_uncased_bhavesh1609_pipeline_en_5.5.0_3.0_1725730984566.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_bhavesh1609_pipeline_en_5.5.0_3.0_1725730984566.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_bhavesh1609_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_bhavesh1609_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_bhavesh1609_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Bhavesh1609/distilbert-base-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_biored_augmented_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_biored_augmented_en.md
new file mode 100644
index 00000000000000..930b783eb26719
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_biored_augmented_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_biored_augmented DistilBertForTokenClassification from Dagobert42
+author: John Snow Labs
+name: distilbert_base_uncased_biored_augmented
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_biored_augmented` is a English model originally trained by Dagobert42.
+
+{:.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/distilbert_base_uncased_biored_augmented_en_5.5.0_3.0_1725739255995.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_biored_augmented_en_5.5.0_3.0_1725739255995.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_biored_augmented","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_biored_augmented", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_biored_augmented|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|248.7 MB|
+
+## References
+
+https://huggingface.co/Dagobert42/distilbert-base-uncased-biored-augmented
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_distilled_clinc_saqidr_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_distilled_clinc_saqidr_en.md
new file mode 100644
index 00000000000000..3f6e4adb4d4046
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_distilled_clinc_saqidr_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_distilled_clinc_saqidr DistilBertForSequenceClassification from saqidr
+author: John Snow Labs
+name: distilbert_base_uncased_distilled_clinc_saqidr
+date: 2024-09-07
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_distilled_clinc_saqidr` is a English model originally trained by saqidr.
+
+{:.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/distilbert_base_uncased_distilled_clinc_saqidr_en_5.5.0_3.0_1725675067996.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_distilled_clinc_saqidr_en_5.5.0_3.0_1725675067996.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_distilled_clinc_saqidr","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_distilled_clinc_saqidr", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_distilled_clinc_saqidr|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.9 MB|
+
+## References
+
+https://huggingface.co/saqidr/distilbert-base-uncased-distilled-clinc
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_distilled_clinc_schnatz65_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_distilled_clinc_schnatz65_pipeline_en.md
new file mode 100644
index 00000000000000..8fb264cd3ce19c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_distilled_clinc_schnatz65_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_distilled_clinc_schnatz65_pipeline pipeline DistilBertForSequenceClassification from Schnatz65
+author: John Snow Labs
+name: distilbert_base_uncased_distilled_clinc_schnatz65_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_distilled_clinc_schnatz65_pipeline` is a English model originally trained by Schnatz65.
+
+{:.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/distilbert_base_uncased_distilled_clinc_schnatz65_pipeline_en_5.5.0_3.0_1725674563559.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_distilled_clinc_schnatz65_pipeline_en_5.5.0_3.0_1725674563559.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_distilled_clinc_schnatz65_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_distilled_clinc_schnatz65_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_distilled_clinc_schnatz65_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.9 MB|
+
+## References
+
+https://huggingface.co/Schnatz65/distilbert-base-uncased-distilled-clinc
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_clinc_jeremygf_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_clinc_jeremygf_pipeline_en.md
new file mode 100644
index 00000000000000..ca35621e2fd1fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_clinc_jeremygf_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_clinc_jeremygf_pipeline pipeline DistilBertForSequenceClassification from jeremygf
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_clinc_jeremygf_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_clinc_jeremygf_pipeline` is a English model originally trained by jeremygf.
+
+{:.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/distilbert_base_uncased_finetuned_clinc_jeremygf_pipeline_en_5.5.0_3.0_1725674845087.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_clinc_jeremygf_pipeline_en_5.5.0_3.0_1725674845087.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_clinc_jeremygf_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_clinc_jeremygf_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_clinc_jeremygf_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.9 MB|
+
+## References
+
+https://huggingface.co/jeremygf/distilbert-base-uncased-finetuned-clinc
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_clinc_jiali_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_clinc_jiali_pipeline_en.md
new file mode 100644
index 00000000000000..2de1a7ab2ff0dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_clinc_jiali_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_clinc_jiali_pipeline pipeline DistilBertForSequenceClassification from Jiali
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_clinc_jiali_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_clinc_jiali_pipeline` is a English model originally trained by Jiali.
+
+{:.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/distilbert_base_uncased_finetuned_clinc_jiali_pipeline_en_5.5.0_3.0_1725674777549.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_clinc_jiali_pipeline_en_5.5.0_3.0_1725674777549.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_clinc_jiali_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_clinc_jiali_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_clinc_jiali_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.9 MB|
+
+## References
+
+https://huggingface.co/Jiali/distilbert-base-uncased-finetuned-clinc
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_con_dataset_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_con_dataset_pipeline_en.md
new file mode 100644
index 00000000000000..216c26d57019c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_con_dataset_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_con_dataset_pipeline pipeline DistilBertForTokenClassification from Emmanuelalo52
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_con_dataset_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_con_dataset_pipeline` is a English model originally trained by Emmanuelalo52.
+
+{:.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/distilbert_base_uncased_finetuned_con_dataset_pipeline_en_5.5.0_3.0_1725730157745.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_con_dataset_pipeline_en_5.5.0_3.0_1725730157745.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_con_dataset_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_con_dataset_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_con_dataset_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Emmanuelalo52/distilbert-base-uncased-finetuned-con-dataset
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_imdb_cervino44_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_imdb_cervino44_en.md
new file mode 100644
index 00000000000000..1cde7c7864005d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_imdb_cervino44_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_cervino44 DistilBertEmbeddings from cervino44
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_cervino44
+date: 2024-09-07
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_cervino44` is a English model originally trained by cervino44.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_cervino44_en_5.5.0_3.0_1725742433783.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_cervino44_en_5.5.0_3.0_1725742433783.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_cervino44","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_cervino44","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_cervino44|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/cervino44/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_imdb_cervino44_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_imdb_cervino44_pipeline_en.md
new file mode 100644
index 00000000000000..d2e6795320437c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_imdb_cervino44_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_cervino44_pipeline pipeline DistilBertEmbeddings from cervino44
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_cervino44_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_cervino44_pipeline` is a English model originally trained by cervino44.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_cervino44_pipeline_en_5.5.0_3.0_1725742445149.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_cervino44_pipeline_en_5.5.0_3.0_1725742445149.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_cervino44_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_cervino44_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_cervino44_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/cervino44/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_imdb_dangurangu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_imdb_dangurangu_pipeline_en.md
new file mode 100644
index 00000000000000..32ce1c260e23b8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_imdb_dangurangu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_dangurangu_pipeline pipeline DistilBertEmbeddings from Dangurangu
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_dangurangu_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_dangurangu_pipeline` is a English model originally trained by Dangurangu.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_dangurangu_pipeline_en_5.5.0_3.0_1725742287017.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_dangurangu_pipeline_en_5.5.0_3.0_1725742287017.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_dangurangu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_dangurangu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_dangurangu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Dangurangu/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_imdb_jinq047_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_imdb_jinq047_en.md
new file mode 100644
index 00000000000000..4f383788c93599
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_imdb_jinq047_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_jinq047 DistilBertEmbeddings from jinq047
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_jinq047
+date: 2024-09-07
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_jinq047` is a English model originally trained by jinq047.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_jinq047_en_5.5.0_3.0_1725742545123.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_jinq047_en_5.5.0_3.0_1725742545123.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_jinq047","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_jinq047","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_jinq047|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/jinq047/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_ner_owenk1212_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_ner_owenk1212_en.md
new file mode 100644
index 00000000000000..ff29d9a84694de
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_ner_owenk1212_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_owenk1212 DistilBertForTokenClassification from OwenK1212
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_owenk1212
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_owenk1212` is a English model originally trained by OwenK1212.
+
+{:.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/distilbert_base_uncased_finetuned_ner_owenk1212_en_5.5.0_3.0_1725739301976.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_owenk1212_en_5.5.0_3.0_1725739301976.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_owenk1212","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_owenk1212", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_owenk1212|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|248.1 MB|
+
+## References
+
+https://huggingface.co/OwenK1212/distilbert-base-uncased-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_ner_perriewang_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_ner_perriewang_pipeline_en.md
new file mode 100644
index 00000000000000..bb63f3f907b828
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_ner_perriewang_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_perriewang_pipeline pipeline DistilBertForTokenClassification from Perriewang
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_perriewang_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_perriewang_pipeline` is a English model originally trained by Perriewang.
+
+{:.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/distilbert_base_uncased_finetuned_ner_perriewang_pipeline_en_5.5.0_3.0_1725730711870.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_perriewang_pipeline_en_5.5.0_3.0_1725730711870.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_perriewang_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_perriewang_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_perriewang_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Perriewang/distilbert-base-uncased-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_ner_sneha_rmh_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_ner_sneha_rmh_pipeline_en.md
new file mode 100644
index 00000000000000..c4c68fd35341e2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_ner_sneha_rmh_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_sneha_rmh_pipeline pipeline DistilBertForTokenClassification from sneha-rmh
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_sneha_rmh_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_sneha_rmh_pipeline` is a English model originally trained by sneha-rmh.
+
+{:.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/distilbert_base_uncased_finetuned_ner_sneha_rmh_pipeline_en_5.5.0_3.0_1725739704382.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_sneha_rmh_pipeline_en_5.5.0_3.0_1725739704382.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_sneha_rmh_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_sneha_rmh_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_sneha_rmh_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/sneha-rmh/distilbert-base-uncased-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_squad_begoniabcs_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_squad_begoniabcs_en.md
new file mode 100644
index 00000000000000..a334767dd2affd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_squad_begoniabcs_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_begoniabcs DistilBertForQuestionAnswering from begoniabcs
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_begoniabcs
+date: 2024-09-07
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_begoniabcs` is a English model originally trained by begoniabcs.
+
+{:.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/distilbert_base_uncased_finetuned_squad_begoniabcs_en_5.5.0_3.0_1725745979737.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_begoniabcs_en_5.5.0_3.0_1725745979737.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_begoniabcs","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_begoniabcs", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_begoniabcs|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/begoniabcs/distilbert-base-uncased-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_squad_carels_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_squad_carels_pipeline_en.md
new file mode 100644
index 00000000000000..a15e61ba058bc4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_squad_carels_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_carels_pipeline pipeline DistilBertForQuestionAnswering from CarelS
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_carels_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_carels_pipeline` is a English model originally trained by CarelS.
+
+{:.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/distilbert_base_uncased_finetuned_squad_carels_pipeline_en_5.5.0_3.0_1725735890356.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_carels_pipeline_en_5.5.0_3.0_1725735890356.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_carels_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_carels_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_carels_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/CarelS/distilbert-base-uncased-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_squad_dataprincess_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_squad_dataprincess_en.md
new file mode 100644
index 00000000000000..36d966883ce714
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_squad_dataprincess_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_dataprincess DistilBertForQuestionAnswering from dataprincess
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_dataprincess
+date: 2024-09-07
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_dataprincess` is a English model originally trained by dataprincess.
+
+{:.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/distilbert_base_uncased_finetuned_squad_dataprincess_en_5.5.0_3.0_1725722933225.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_dataprincess_en_5.5.0_3.0_1725722933225.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_dataprincess","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_dataprincess", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_dataprincess|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.9 MB|
+
+## References
+
+https://huggingface.co/dataprincess/distilbert-base-uncased-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_squad_ep8_batch16_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_squad_ep8_batch16_pipeline_en.md
new file mode 100644
index 00000000000000..d598033caaa07b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_squad_ep8_batch16_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_ep8_batch16_pipeline pipeline DistilBertForQuestionAnswering from wieheistdu
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_ep8_batch16_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_ep8_batch16_pipeline` is a English model originally trained by wieheistdu.
+
+{:.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/distilbert_base_uncased_finetuned_squad_ep8_batch16_pipeline_en_5.5.0_3.0_1725736070501.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_ep8_batch16_pipeline_en_5.5.0_3.0_1725736070501.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_ep8_batch16_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_ep8_batch16_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_ep8_batch16_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/wieheistdu/distilbert-base-uncased-finetuned-squad-ep8-batch16
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_squad_foma_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_squad_foma_en.md
new file mode 100644
index 00000000000000..50de2144daec60
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_squad_foma_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_foma DistilBertForQuestionAnswering from Foma
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_foma
+date: 2024-09-07
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_foma` is a English model originally trained by Foma.
+
+{:.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/distilbert_base_uncased_finetuned_squad_foma_en_5.5.0_3.0_1725736212910.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_foma_en_5.5.0_3.0_1725736212910.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_foma","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_foma", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_foma|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Foma/distilbert-base-uncased-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_squad_foma_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_squad_foma_pipeline_en.md
new file mode 100644
index 00000000000000..1bfa03a1909c1c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_squad_foma_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_foma_pipeline pipeline DistilBertForQuestionAnswering from Foma
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_foma_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_foma_pipeline` is a English model originally trained by Foma.
+
+{:.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/distilbert_base_uncased_finetuned_squad_foma_pipeline_en_5.5.0_3.0_1725736224966.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_foma_pipeline_en_5.5.0_3.0_1725736224966.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_foma_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_foma_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_foma_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Foma/distilbert-base-uncased-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_squad_meline_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_squad_meline_pipeline_en.md
new file mode 100644
index 00000000000000..54fae6967e9898
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_squad_meline_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_meline_pipeline pipeline DistilBertForQuestionAnswering from Meline
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_meline_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_meline_pipeline` is a English model originally trained by Meline.
+
+{:.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/distilbert_base_uncased_finetuned_squad_meline_pipeline_en_5.5.0_3.0_1725746272147.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_meline_pipeline_en_5.5.0_3.0_1725746272147.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_meline_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_meline_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_meline_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.4 MB|
+
+## References
+
+https://huggingface.co/Meline/distilbert-base-uncased-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_squad_sasa3396_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_squad_sasa3396_pipeline_en.md
new file mode 100644
index 00000000000000..09484920a86670
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_squad_sasa3396_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_sasa3396_pipeline pipeline DistilBertForQuestionAnswering from sasa3396
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_sasa3396_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_sasa3396_pipeline` is a English model originally trained by sasa3396.
+
+{:.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/distilbert_base_uncased_finetuned_squad_sasa3396_pipeline_en_5.5.0_3.0_1725746326620.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_sasa3396_pipeline_en_5.5.0_3.0_1725746326620.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_sasa3396_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_sasa3396_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_sasa3396_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/sasa3396/distilbert-base-uncased-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_squad_ucmp137538_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_squad_ucmp137538_en.md
new file mode 100644
index 00000000000000..2cd0e7dd255336
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_squad_ucmp137538_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_ucmp137538 DistilBertForQuestionAnswering from ucmp137538
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_ucmp137538
+date: 2024-09-07
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_ucmp137538` is a English model originally trained by ucmp137538.
+
+{:.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/distilbert_base_uncased_finetuned_squad_ucmp137538_en_5.5.0_3.0_1725735769959.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_ucmp137538_en_5.5.0_3.0_1725735769959.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_ucmp137538","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_ucmp137538", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_ucmp137538|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/ucmp137538/distilbert-base-uncased-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_wikiann_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_wikiann_en.md
new file mode 100644
index 00000000000000..04071d14e30c3b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_finetuned_wikiann_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_wikiann DistilBertForTokenClassification from hannahisrael03
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_wikiann
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_wikiann` is a English model originally trained by hannahisrael03.
+
+{:.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/distilbert_base_uncased_finetuned_wikiann_en_5.5.0_3.0_1725729772507.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_wikiann_en_5.5.0_3.0_1725729772507.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_wikiann","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_wikiann", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_wikiann|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/hannahisrael03/distilbert-base-uncased-finetuned-wikiann
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_pii_200_devtibo_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_pii_200_devtibo_pipeline_en.md
new file mode 100644
index 00000000000000..5c74b8fc95eb99
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_pii_200_devtibo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_pii_200_devtibo_pipeline pipeline DistilBertForTokenClassification from devtibo
+author: John Snow Labs
+name: distilbert_base_uncased_pii_200_devtibo_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_pii_200_devtibo_pipeline` is a English model originally trained by devtibo.
+
+{:.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/distilbert_base_uncased_pii_200_devtibo_pipeline_en_5.5.0_3.0_1725730062969.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_pii_200_devtibo_pipeline_en_5.5.0_3.0_1725730062969.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_pii_200_devtibo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_pii_200_devtibo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_pii_200_devtibo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.6 MB|
+
+## References
+
+https://huggingface.co/devtibo/distilbert-base-uncased-pii-200
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_squad2_p15_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_squad2_p15_en.md
new file mode 100644
index 00000000000000..31a9c00a1c2abe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_squad2_p15_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_base_uncased_squad2_p15 DistilBertForQuestionAnswering from pminha
+author: John Snow Labs
+name: distilbert_base_uncased_squad2_p15
+date: 2024-09-07
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_squad2_p15` is a English model originally trained by pminha.
+
+{:.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/distilbert_base_uncased_squad2_p15_en_5.5.0_3.0_1725727441587.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_squad2_p15_en_5.5.0_3.0_1725727441587.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_squad2_p15","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_squad2_p15", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_squad2_p15|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|231.5 MB|
+
+## References
+
+https://huggingface.co/pminha/distilbert-base-uncased-squad2-p15
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_wnut_17_full_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_wnut_17_full_pipeline_en.md
new file mode 100644
index 00000000000000..caec4855a9a710
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_base_uncased_wnut_17_full_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_wnut_17_full_pipeline pipeline DistilBertForTokenClassification from yefo-ufpe
+author: John Snow Labs
+name: distilbert_base_uncased_wnut_17_full_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_wnut_17_full_pipeline` is a English model originally trained by yefo-ufpe.
+
+{:.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/distilbert_base_uncased_wnut_17_full_pipeline_en_5.5.0_3.0_1725730752459.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_wnut_17_full_pipeline_en_5.5.0_3.0_1725730752459.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_wnut_17_full_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_wnut_17_full_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_wnut_17_full_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/yefo-ufpe/distilbert-base-uncased-wnut_17-full
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_emotion_mudogruer_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_emotion_mudogruer_pipeline_en.md
new file mode 100644
index 00000000000000..f8c6d1d6e41d2a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_emotion_mudogruer_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_emotion_mudogruer_pipeline pipeline DistilBertForSequenceClassification from mudogruer
+author: John Snow Labs
+name: distilbert_emotion_mudogruer_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_emotion_mudogruer_pipeline` is a English model originally trained by mudogruer.
+
+{:.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/distilbert_emotion_mudogruer_pipeline_en_5.5.0_3.0_1725674540412.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_emotion_mudogruer_pipeline_en_5.5.0_3.0_1725674540412.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
+
+pipeline = PretrainedPipeline("distilbert_emotion_mudogruer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_emotion_mudogruer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_emotion_mudogruer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/mudogruer/distilbert-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_finetuned_ai4privacy_token_classification_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_finetuned_ai4privacy_token_classification_en.md
new file mode 100644
index 00000000000000..7d609618db36dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_finetuned_ai4privacy_token_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_finetuned_ai4privacy_token_classification DistilBertForTokenClassification from neelgokhale
+author: John Snow Labs
+name: distilbert_finetuned_ai4privacy_token_classification
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_ai4privacy_token_classification` is a English model originally trained by neelgokhale.
+
+{:.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/distilbert_finetuned_ai4privacy_token_classification_en_5.5.0_3.0_1725729993604.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_ai4privacy_token_classification_en_5.5.0_3.0_1725729993604.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_finetuned_ai4privacy_token_classification","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_finetuned_ai4privacy_token_classification", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_ai4privacy_token_classification|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.6 MB|
+
+## References
+
+https://huggingface.co/neelgokhale/distilbert_finetuned_ai4privacy_token_classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_kazakh_ner_2_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_kazakh_ner_2_en.md
new file mode 100644
index 00000000000000..d23f5c3ae3cd2f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_kazakh_ner_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_kazakh_ner_2 DistilBertForTokenClassification from yasminsur
+author: John Snow Labs
+name: distilbert_kazakh_ner_2
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_kazakh_ner_2` is a English model originally trained by yasminsur.
+
+{:.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/distilbert_kazakh_ner_2_en_5.5.0_3.0_1725730778208.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_kazakh_ner_2_en_5.5.0_3.0_1725730778208.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_kazakh_ner_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_kazakh_ner_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_kazakh_ner_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|505.5 MB|
+
+## References
+
+https://huggingface.co/yasminsur/distilbert-kazakh-ner-2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_ner_andrembcosta_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_ner_andrembcosta_en.md
new file mode 100644
index 00000000000000..917bdffd841427
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_ner_andrembcosta_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_ner_andrembcosta DistilBertForTokenClassification from andrembcosta
+author: John Snow Labs
+name: distilbert_ner_andrembcosta
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ner_andrembcosta` is a English model originally trained by andrembcosta.
+
+{:.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/distilbert_ner_andrembcosta_en_5.5.0_3.0_1725731210919.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ner_andrembcosta_en_5.5.0_3.0_1725731210919.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_ner_andrembcosta","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_ner_andrembcosta", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_ner_andrembcosta|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/andrembcosta/distilbert-NER
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_ner_andrembcosta_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_ner_andrembcosta_pipeline_en.md
new file mode 100644
index 00000000000000..7a54e00a26669c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_ner_andrembcosta_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_ner_andrembcosta_pipeline pipeline DistilBertForTokenClassification from andrembcosta
+author: John Snow Labs
+name: distilbert_ner_andrembcosta_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ner_andrembcosta_pipeline` is a English model originally trained by andrembcosta.
+
+{:.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/distilbert_ner_andrembcosta_pipeline_en_5.5.0_3.0_1725731222491.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ner_andrembcosta_pipeline_en_5.5.0_3.0_1725731222491.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
+
+pipeline = PretrainedPipeline("distilbert_ner_andrembcosta_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_ner_andrembcosta_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_ner_andrembcosta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/andrembcosta/distilbert-NER
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_qasports_basketball_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_qasports_basketball_pipeline_en.md
new file mode 100644
index 00000000000000..5344918be82958
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_qasports_basketball_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_qasports_basketball_pipeline pipeline DistilBertForQuestionAnswering from laurafcamargos
+author: John Snow Labs
+name: distilbert_qasports_basketball_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_qasports_basketball_pipeline` is a English model originally trained by laurafcamargos.
+
+{:.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/distilbert_qasports_basketball_pipeline_en_5.5.0_3.0_1725727627148.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_qasports_basketball_pipeline_en_5.5.0_3.0_1725727627148.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
+
+pipeline = PretrainedPipeline("distilbert_qasports_basketball_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_qasports_basketball_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_qasports_basketball_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/laurafcamargos/distilbert-qasports-basketball
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_squad_dofla_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_squad_dofla_pipeline_en.md
new file mode 100644
index 00000000000000..75c0dbd9348312
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_squad_dofla_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_squad_dofla_pipeline pipeline DistilBertForQuestionAnswering from Dofla
+author: John Snow Labs
+name: distilbert_squad_dofla_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_squad_dofla_pipeline` is a English model originally trained by Dofla.
+
+{:.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/distilbert_squad_dofla_pipeline_en_5.5.0_3.0_1725735884870.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_squad_dofla_pipeline_en_5.5.0_3.0_1725735884870.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
+
+pipeline = PretrainedPipeline("distilbert_squad_dofla_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_squad_dofla_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_squad_dofla_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Dofla/distilbert-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilbert_twitter_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilbert_twitter_en.md
new file mode 100644
index 00000000000000..5b6c46f539fdcc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilbert_twitter_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_twitter DistilBertForSequenceClassification from minhcrafters
+author: John Snow Labs
+name: distilbert_twitter
+date: 2024-09-07
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_twitter` is a English model originally trained by minhcrafters.
+
+{:.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/distilbert_twitter_en_5.5.0_3.0_1725674556311.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_twitter_en_5.5.0_3.0_1725674556311.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_twitter","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_twitter", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_twitter|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/minhcrafters/distilbert-twitter
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distillbert_finetuned_finer_4_v3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-distillbert_finetuned_finer_4_v3_pipeline_en.md
new file mode 100644
index 00000000000000..95cb82cb7ec12a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distillbert_finetuned_finer_4_v3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distillbert_finetuned_finer_4_v3_pipeline pipeline DistilBertForTokenClassification from ShadyML
+author: John Snow Labs
+name: distillbert_finetuned_finer_4_v3_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distillbert_finetuned_finer_4_v3_pipeline` is a English model originally trained by ShadyML.
+
+{:.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/distillbert_finetuned_finer_4_v3_pipeline_en_5.5.0_3.0_1725729898894.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distillbert_finetuned_finer_4_v3_pipeline_en_5.5.0_3.0_1725729898894.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
+
+pipeline = PretrainedPipeline("distillbert_finetuned_finer_4_v3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distillbert_finetuned_finer_4_v3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distillbert_finetuned_finer_4_v3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/ShadyML/distillbert-finetuned-finer-4-v3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-distilroberta_base_climate_d_s_en.md b/docs/_posts/ahmedlone127/2024-09-07-distilroberta_base_climate_d_s_en.md
new file mode 100644
index 00000000000000..142cf58362c72e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-distilroberta_base_climate_d_s_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilroberta_base_climate_d_s RoBertaEmbeddings from climatebert
+author: John Snow Labs
+name: distilroberta_base_climate_d_s
+date: 2024-09-07
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_climate_d_s` is a English model originally trained by climatebert.
+
+{:.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/distilroberta_base_climate_d_s_en_5.5.0_3.0_1725697883077.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_climate_d_s_en_5.5.0_3.0_1725697883077.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_climate_d_s","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_climate_d_s","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_climate_d_s|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|307.4 MB|
+
+## References
+
+https://huggingface.co/climatebert/distilroberta-base-climate-d-s
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-dummy_model_arunm7_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-dummy_model_arunm7_pipeline_en.md
new file mode 100644
index 00000000000000..426882a925b881
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-dummy_model_arunm7_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_arunm7_pipeline pipeline CamemBertEmbeddings from ArunM7
+author: John Snow Labs
+name: dummy_model_arunm7_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_arunm7_pipeline` is a English model originally trained by ArunM7.
+
+{:.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/dummy_model_arunm7_pipeline_en_5.5.0_3.0_1725728946549.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_arunm7_pipeline_en_5.5.0_3.0_1725728946549.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
+
+pipeline = PretrainedPipeline("dummy_model_arunm7_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_arunm7_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_arunm7_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/ArunM7/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-dummy_model_linyi_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-dummy_model_linyi_pipeline_en.md
new file mode 100644
index 00000000000000..006a2a545e2272
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-dummy_model_linyi_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_linyi_pipeline pipeline CamemBertEmbeddings from linyi
+author: John Snow Labs
+name: dummy_model_linyi_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_linyi_pipeline` is a English model originally trained by linyi.
+
+{:.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/dummy_model_linyi_pipeline_en_5.5.0_3.0_1725728278664.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_linyi_pipeline_en_5.5.0_3.0_1725728278664.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
+
+pipeline = PretrainedPipeline("dummy_model_linyi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_linyi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_linyi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/linyi/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-dummy_model_luis_d_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-dummy_model_luis_d_pipeline_en.md
new file mode 100644
index 00000000000000..0f5a781355bda3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-dummy_model_luis_d_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_luis_d_pipeline pipeline CamemBertEmbeddings from Luis-d
+author: John Snow Labs
+name: dummy_model_luis_d_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_luis_d_pipeline` is a English model originally trained by Luis-d.
+
+{:.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/dummy_model_luis_d_pipeline_en_5.5.0_3.0_1725728547497.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_luis_d_pipeline_en_5.5.0_3.0_1725728547497.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
+
+pipeline = PretrainedPipeline("dummy_model_luis_d_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_luis_d_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_luis_d_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Luis-d/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-dummy_model_memegha_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-dummy_model_memegha_pipeline_en.md
new file mode 100644
index 00000000000000..12afeedb2e3ed5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-dummy_model_memegha_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_memegha_pipeline pipeline CamemBertEmbeddings from memegha
+author: John Snow Labs
+name: dummy_model_memegha_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_memegha_pipeline` is a English model originally trained by memegha.
+
+{:.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/dummy_model_memegha_pipeline_en_5.5.0_3.0_1725729409817.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_memegha_pipeline_en_5.5.0_3.0_1725729409817.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
+
+pipeline = PretrainedPipeline("dummy_model_memegha_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_memegha_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_memegha_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/memegha/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-dummy_model_rinkorn_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-dummy_model_rinkorn_pipeline_en.md
new file mode 100644
index 00000000000000..1e46732d2724f2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-dummy_model_rinkorn_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_rinkorn_pipeline pipeline CamemBertEmbeddings from rinkorn
+author: John Snow Labs
+name: dummy_model_rinkorn_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_rinkorn_pipeline` is a English model originally trained by rinkorn.
+
+{:.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/dummy_model_rinkorn_pipeline_en_5.5.0_3.0_1725728959656.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_rinkorn_pipeline_en_5.5.0_3.0_1725728959656.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
+
+pipeline = PretrainedPipeline("dummy_model_rinkorn_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_rinkorn_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_rinkorn_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/rinkorn/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-dummy_model_rudytzhan_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-dummy_model_rudytzhan_pipeline_en.md
new file mode 100644
index 00000000000000..74dbc0495fce88
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-dummy_model_rudytzhan_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_rudytzhan_pipeline pipeline CamemBertEmbeddings from rudyTzhan
+author: John Snow Labs
+name: dummy_model_rudytzhan_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_rudytzhan_pipeline` is a English model originally trained by rudyTzhan.
+
+{:.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/dummy_model_rudytzhan_pipeline_en_5.5.0_3.0_1725729362705.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_rudytzhan_pipeline_en_5.5.0_3.0_1725729362705.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
+
+pipeline = PretrainedPipeline("dummy_model_rudytzhan_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_rudytzhan_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_rudytzhan_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/rudyTzhan/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-dummy_model_sidd_2203_en.md b/docs/_posts/ahmedlone127/2024-09-07-dummy_model_sidd_2203_en.md
new file mode 100644
index 00000000000000..33578e90bed768
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-dummy_model_sidd_2203_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_sidd_2203 CamemBertEmbeddings from sidd-2203
+author: John Snow Labs
+name: dummy_model_sidd_2203
+date: 2024-09-07
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_sidd_2203` is a English model originally trained by sidd-2203.
+
+{:.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/dummy_model_sidd_2203_en_5.5.0_3.0_1725729190487.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_sidd_2203_en_5.5.0_3.0_1725729190487.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_sidd_2203","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_sidd_2203","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_sidd_2203|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/sidd-2203/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-ecommerce_ner_en.md b/docs/_posts/ahmedlone127/2024-09-07-ecommerce_ner_en.md
new file mode 100644
index 00000000000000..b607e9da3ef4a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-ecommerce_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ecommerce_ner DistilBertForTokenClassification from mach-12
+author: John Snow Labs
+name: ecommerce_ner
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ecommerce_ner` is a English model originally trained by mach-12.
+
+{:.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/ecommerce_ner_en_5.5.0_3.0_1725730447281.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ecommerce_ner_en_5.5.0_3.0_1725730447281.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("ecommerce_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("ecommerce_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ecommerce_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/mach-12/ecommerce-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-embedding_finetuned_model_v2_en.md b/docs/_posts/ahmedlone127/2024-09-07-embedding_finetuned_model_v2_en.md
new file mode 100644
index 00000000000000..460da59ebd53ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-embedding_finetuned_model_v2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English embedding_finetuned_model_v2 MPNetEmbeddings from phoenixSP
+author: John Snow Labs
+name: embedding_finetuned_model_v2
+date: 2024-09-07
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`embedding_finetuned_model_v2` is a English model originally trained by phoenixSP.
+
+{:.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/embedding_finetuned_model_v2_en_5.5.0_3.0_1725703696909.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/embedding_finetuned_model_v2_en_5.5.0_3.0_1725703696909.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("embedding_finetuned_model_v2","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("embedding_finetuned_model_v2","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|embedding_finetuned_model_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/phoenixSP/embedding-finetuned-model-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-entity_rec_en.md b/docs/_posts/ahmedlone127/2024-09-07-entity_rec_en.md
new file mode 100644
index 00000000000000..7a6f0f4607d560
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-entity_rec_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English entity_rec DistilBertForTokenClassification from cleopatro
+author: John Snow Labs
+name: entity_rec
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`entity_rec` is a English model originally trained by cleopatro.
+
+{:.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/entity_rec_en_5.5.0_3.0_1725734116610.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/entity_rec_en_5.5.0_3.0_1725734116610.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("entity_rec","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("entity_rec", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|entity_rec|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/cleopatro/Entity_Rec
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-envroberta_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-envroberta_base_pipeline_en.md
new file mode 100644
index 00000000000000..cac20143b5584f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-envroberta_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English envroberta_base_pipeline pipeline RoBertaEmbeddings from ESGBERT
+author: John Snow Labs
+name: envroberta_base_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`envroberta_base_pipeline` is a English model originally trained by ESGBERT.
+
+{:.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/envroberta_base_pipeline_en_5.5.0_3.0_1725673454888.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/envroberta_base_pipeline_en_5.5.0_3.0_1725673454888.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
+
+pipeline = PretrainedPipeline("envroberta_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("envroberta_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|envroberta_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/ESGBERT/EnvRoBERTa-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-esmlmt60_10000_en.md b/docs/_posts/ahmedlone127/2024-09-07-esmlmt60_10000_en.md
new file mode 100644
index 00000000000000..a6a61cecf2687b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-esmlmt60_10000_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English esmlmt60_10000 BertEmbeddings from hjkim811
+author: John Snow Labs
+name: esmlmt60_10000
+date: 2024-09-07
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`esmlmt60_10000` is a English model originally trained by hjkim811.
+
+{:.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/esmlmt60_10000_en_5.5.0_3.0_1725675355811.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esmlmt60_10000_en_5.5.0_3.0_1725675355811.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("esmlmt60_10000","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("esmlmt60_10000","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|esmlmt60_10000|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/hjkim811/esmlmt60-10000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-esmlmt62_2500_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-esmlmt62_2500_pipeline_en.md
new file mode 100644
index 00000000000000..0a47d45e074f3f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-esmlmt62_2500_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English esmlmt62_2500_pipeline pipeline BertEmbeddings from hjkim811
+author: John Snow Labs
+name: esmlmt62_2500_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`esmlmt62_2500_pipeline` is a English model originally trained by hjkim811.
+
+{:.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/esmlmt62_2500_pipeline_en_5.5.0_3.0_1725675907048.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esmlmt62_2500_pipeline_en_5.5.0_3.0_1725675907048.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
+
+pipeline = PretrainedPipeline("esmlmt62_2500_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("esmlmt62_2500_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|esmlmt62_2500_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/hjkim811/esmlmt62-2500
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-example_qa_model_en.md b/docs/_posts/ahmedlone127/2024-09-07-example_qa_model_en.md
new file mode 100644
index 00000000000000..7c2586e3c57629
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-example_qa_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English example_qa_model DistilBertForQuestionAnswering from vodiylik
+author: John Snow Labs
+name: example_qa_model
+date: 2024-09-07
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`example_qa_model` is a English model originally trained by vodiylik.
+
+{:.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/example_qa_model_en_5.5.0_3.0_1725735780224.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/example_qa_model_en_5.5.0_3.0_1725735780224.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("example_qa_model","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("example_qa_model", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|example_qa_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/vodiylik/example_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-fabner_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-fabner_ner_pipeline_en.md
new file mode 100644
index 00000000000000..bc3feb9286d6dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-fabner_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English fabner_ner_pipeline pipeline DistilBertForTokenClassification from kalexa2
+author: John Snow Labs
+name: fabner_ner_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fabner_ner_pipeline` is a English model originally trained by kalexa2.
+
+{:.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/fabner_ner_pipeline_en_5.5.0_3.0_1725731135881.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fabner_ner_pipeline_en_5.5.0_3.0_1725731135881.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
+
+pipeline = PretrainedPipeline("fabner_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fabner_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fabner_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|244.0 MB|
+
+## References
+
+https://huggingface.co/kalexa2/fabner-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-fewshot_qa_002_20230622_001_en.md b/docs/_posts/ahmedlone127/2024-09-07-fewshot_qa_002_20230622_001_en.md
new file mode 100644
index 00000000000000..da0f1eaeca293a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-fewshot_qa_002_20230622_001_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English fewshot_qa_002_20230622_001 XlmRoBertaForQuestionAnswering from intanm
+author: John Snow Labs
+name: fewshot_qa_002_20230622_001
+date: 2024-09-07
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fewshot_qa_002_20230622_001` is a English model originally trained by intanm.
+
+{:.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/fewshot_qa_002_20230622_001_en_5.5.0_3.0_1725686094477.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fewshot_qa_002_20230622_001_en_5.5.0_3.0_1725686094477.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("fewshot_qa_002_20230622_001","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("fewshot_qa_002_20230622_001", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fewshot_qa_002_20230622_001|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|880.1 MB|
+
+## References
+
+https://huggingface.co/intanm/fewshot-qa-002-20230622-001
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-fg_codebert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-fg_codebert_pipeline_en.md
new file mode 100644
index 00000000000000..a64545d556e371
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-fg_codebert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English fg_codebert_pipeline pipeline RoBertaEmbeddings from NTUYG
+author: John Snow Labs
+name: fg_codebert_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fg_codebert_pipeline` is a English model originally trained by NTUYG.
+
+{:.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/fg_codebert_pipeline_en_5.5.0_3.0_1725678852757.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fg_codebert_pipeline_en_5.5.0_3.0_1725678852757.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
+
+pipeline = PretrainedPipeline("fg_codebert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fg_codebert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fg_codebert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.1 MB|
+
+## References
+
+https://huggingface.co/NTUYG/FG-CodeBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-fine_tune_llm_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-fine_tune_llm_pipeline_en.md
new file mode 100644
index 00000000000000..08ac70d4ff10ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-fine_tune_llm_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fine_tune_llm_pipeline pipeline DistilBertForQuestionAnswering from SaiSaketh
+author: John Snow Labs
+name: fine_tune_llm_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tune_llm_pipeline` is a English model originally trained by SaiSaketh.
+
+{:.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/fine_tune_llm_pipeline_en_5.5.0_3.0_1725736427913.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tune_llm_pipeline_en_5.5.0_3.0_1725736427913.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
+
+pipeline = PretrainedPipeline("fine_tune_llm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tune_llm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tune_llm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/SaiSaketh/fine_tune_llm
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-fine_tuned_qa_model_bert_en.md b/docs/_posts/ahmedlone127/2024-09-07-fine_tuned_qa_model_bert_en.md
new file mode 100644
index 00000000000000..fdb8c2c9bc077f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-fine_tuned_qa_model_bert_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English fine_tuned_qa_model_bert DistilBertForQuestionAnswering from jayvinay
+author: John Snow Labs
+name: fine_tuned_qa_model_bert
+date: 2024-09-07
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_qa_model_bert` is a English model originally trained by jayvinay.
+
+{:.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/fine_tuned_qa_model_bert_en_5.5.0_3.0_1725736017773.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_qa_model_bert_en_5.5.0_3.0_1725736017773.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("fine_tuned_qa_model_bert","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("fine_tuned_qa_model_bert", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_qa_model_bert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/jayvinay/fine-tuned-qa-model-bert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-fine_tuned_qa_model_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-fine_tuned_qa_model_bert_pipeline_en.md
new file mode 100644
index 00000000000000..0acbae140514db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-fine_tuned_qa_model_bert_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fine_tuned_qa_model_bert_pipeline pipeline DistilBertForQuestionAnswering from jayvinay
+author: John Snow Labs
+name: fine_tuned_qa_model_bert_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_qa_model_bert_pipeline` is a English model originally trained by jayvinay.
+
+{:.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/fine_tuned_qa_model_bert_pipeline_en_5.5.0_3.0_1725736030849.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_qa_model_bert_pipeline_en_5.5.0_3.0_1725736030849.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
+
+pipeline = PretrainedPipeline("fine_tuned_qa_model_bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_qa_model_bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_qa_model_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/jayvinay/fine-tuned-qa-model-bert
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-fine_tuned_tradisi_bali_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-fine_tuned_tradisi_bali_pipeline_en.md
new file mode 100644
index 00000000000000..f292cdb9bb2655
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-fine_tuned_tradisi_bali_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English fine_tuned_tradisi_bali_pipeline pipeline DistilBertForQuestionAnswering from SwastyMaharani
+author: John Snow Labs
+name: fine_tuned_tradisi_bali_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_tradisi_bali_pipeline` is a English model originally trained by SwastyMaharani.
+
+{:.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/fine_tuned_tradisi_bali_pipeline_en_5.5.0_3.0_1725727163206.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_tradisi_bali_pipeline_en_5.5.0_3.0_1725727163206.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
+
+pipeline = PretrainedPipeline("fine_tuned_tradisi_bali_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_tradisi_bali_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_tradisi_bali_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/SwastyMaharani/fine-tuned-tradisi-bali
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-finetuned2_ldiego73_en.md b/docs/_posts/ahmedlone127/2024-09-07-finetuned2_ldiego73_en.md
new file mode 100644
index 00000000000000..c7b85e08f897ec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-finetuned2_ldiego73_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English finetuned2_ldiego73 DistilBertForQuestionAnswering from ldiego73
+author: John Snow Labs
+name: finetuned2_ldiego73
+date: 2024-09-07
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned2_ldiego73` is a English model originally trained by ldiego73.
+
+{:.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/finetuned2_ldiego73_en_5.5.0_3.0_1725727360903.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned2_ldiego73_en_5.5.0_3.0_1725727360903.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("finetuned2_ldiego73","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("finetuned2_ldiego73", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned2_ldiego73|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/ldiego73/finetuned2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-finetuned_english_tonga_tonga_islands_vietnamese_pien_27_en.md b/docs/_posts/ahmedlone127/2024-09-07-finetuned_english_tonga_tonga_islands_vietnamese_pien_27_en.md
new file mode 100644
index 00000000000000..c10a44a411f147
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-finetuned_english_tonga_tonga_islands_vietnamese_pien_27_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuned_english_tonga_tonga_islands_vietnamese_pien_27 MarianTransformer from pien-27
+author: John Snow Labs
+name: finetuned_english_tonga_tonga_islands_vietnamese_pien_27
+date: 2024-09-07
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_english_tonga_tonga_islands_vietnamese_pien_27` is a English model originally trained by pien-27.
+
+{:.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/finetuned_english_tonga_tonga_islands_vietnamese_pien_27_en_5.5.0_3.0_1725747925126.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_english_tonga_tonga_islands_vietnamese_pien_27_en_5.5.0_3.0_1725747925126.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("finetuned_english_tonga_tonga_islands_vietnamese_pien_27","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("finetuned_english_tonga_tonga_islands_vietnamese_pien_27","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_english_tonga_tonga_islands_vietnamese_pien_27|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|475.3 MB|
+
+## References
+
+https://huggingface.co/pien-27/finetuned-en-to-vi
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-helsinki_danish_swedish_v12_en.md b/docs/_posts/ahmedlone127/2024-09-07-helsinki_danish_swedish_v12_en.md
new file mode 100644
index 00000000000000..ce11c2b10b0d1d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-helsinki_danish_swedish_v12_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English helsinki_danish_swedish_v12 MarianTransformer from Danieljacobsen
+author: John Snow Labs
+name: helsinki_danish_swedish_v12
+date: 2024-09-07
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`helsinki_danish_swedish_v12` is a English model originally trained by Danieljacobsen.
+
+{:.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/helsinki_danish_swedish_v12_en_5.5.0_3.0_1725741338434.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/helsinki_danish_swedish_v12_en_5.5.0_3.0_1725741338434.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("helsinki_danish_swedish_v12","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("helsinki_danish_swedish_v12","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|helsinki_danish_swedish_v12|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|496.8 MB|
+
+## References
+
+https://huggingface.co/Danieljacobsen/Helsinki-DA-SV-v12
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-helsinki_opus_german_english_fine_tuned_wmt16_finetuned_src_tonga_tonga_islands_trg_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-helsinki_opus_german_english_fine_tuned_wmt16_finetuned_src_tonga_tonga_islands_trg_pipeline_en.md
new file mode 100644
index 00000000000000..58c2ed6adadf22
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-helsinki_opus_german_english_fine_tuned_wmt16_finetuned_src_tonga_tonga_islands_trg_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English helsinki_opus_german_english_fine_tuned_wmt16_finetuned_src_tonga_tonga_islands_trg_pipeline pipeline MarianTransformer from musralina
+author: John Snow Labs
+name: helsinki_opus_german_english_fine_tuned_wmt16_finetuned_src_tonga_tonga_islands_trg_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`helsinki_opus_german_english_fine_tuned_wmt16_finetuned_src_tonga_tonga_islands_trg_pipeline` is a English model originally trained by musralina.
+
+{:.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/helsinki_opus_german_english_fine_tuned_wmt16_finetuned_src_tonga_tonga_islands_trg_pipeline_en_5.5.0_3.0_1725748129907.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/helsinki_opus_german_english_fine_tuned_wmt16_finetuned_src_tonga_tonga_islands_trg_pipeline_en_5.5.0_3.0_1725748129907.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
+
+pipeline = PretrainedPipeline("helsinki_opus_german_english_fine_tuned_wmt16_finetuned_src_tonga_tonga_islands_trg_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("helsinki_opus_german_english_fine_tuned_wmt16_finetuned_src_tonga_tonga_islands_trg_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|helsinki_opus_german_english_fine_tuned_wmt16_finetuned_src_tonga_tonga_islands_trg_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|499.6 MB|
+
+## References
+
+https://huggingface.co/musralina/helsinki-opus-de-en-fine-tuned-wmt16-finetuned-src-to-trg
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-hiner_romanian_large_en.md b/docs/_posts/ahmedlone127/2024-09-07-hiner_romanian_large_en.md
new file mode 100644
index 00000000000000..23cf6f323a0b27
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-hiner_romanian_large_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English hiner_romanian_large RoBertaForTokenClassification from TathagatAgrawal
+author: John Snow Labs
+name: hiner_romanian_large
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hiner_romanian_large` is a English model originally trained by TathagatAgrawal.
+
+{:.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/hiner_romanian_large_en_5.5.0_3.0_1725723845937.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hiner_romanian_large_en_5.5.0_3.0_1725723845937.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("hiner_romanian_large","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("hiner_romanian_large", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hiner_romanian_large|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|425.0 MB|
+
+## References
+
+https://huggingface.co/TathagatAgrawal/HiNER_RO_LARGE
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-intent_global_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-intent_global_pipeline_en.md
new file mode 100644
index 00000000000000..c38b9bc57f5e55
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-intent_global_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English intent_global_pipeline pipeline RoBertaForSequenceClassification from Onebu
+author: John Snow Labs
+name: intent_global_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`intent_global_pipeline` is a English model originally trained by Onebu.
+
+{:.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/intent_global_pipeline_en_5.5.0_3.0_1725718438931.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/intent_global_pipeline_en_5.5.0_3.0_1725718438931.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
+
+pipeline = PretrainedPipeline("intent_global_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("intent_global_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|intent_global_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|420.7 MB|
+
+## References
+
+https://huggingface.co/Onebu/intent-global
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-isom5240_whisper_small_zhhk_1_en.md b/docs/_posts/ahmedlone127/2024-09-07-isom5240_whisper_small_zhhk_1_en.md
new file mode 100644
index 00000000000000..a6299ce89cd3f3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-isom5240_whisper_small_zhhk_1_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English isom5240_whisper_small_zhhk_1 WhisperForCTC from RexChan
+author: John Snow Labs
+name: isom5240_whisper_small_zhhk_1
+date: 2024-09-07
+tags: [en, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`isom5240_whisper_small_zhhk_1` is a English model originally trained by RexChan.
+
+{:.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/isom5240_whisper_small_zhhk_1_en_5.5.0_3.0_1725750251683.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/isom5240_whisper_small_zhhk_1_en_5.5.0_3.0_1725750251683.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
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("isom5240_whisper_small_zhhk_1","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("isom5240_whisper_small_zhhk_1", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|isom5240_whisper_small_zhhk_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/RexChan/ISOM5240-whisper-small-zhhk_1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-kamal_camembert_dummy_nskamal_en.md b/docs/_posts/ahmedlone127/2024-09-07-kamal_camembert_dummy_nskamal_en.md
new file mode 100644
index 00000000000000..e5b3e1e3ae9533
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-kamal_camembert_dummy_nskamal_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English kamal_camembert_dummy_nskamal CamemBertEmbeddings from nskamal
+author: John Snow Labs
+name: kamal_camembert_dummy_nskamal
+date: 2024-09-07
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kamal_camembert_dummy_nskamal` is a English model originally trained by nskamal.
+
+{:.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/kamal_camembert_dummy_nskamal_en_5.5.0_3.0_1725728653049.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kamal_camembert_dummy_nskamal_en_5.5.0_3.0_1725728653049.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("kamal_camembert_dummy_nskamal","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("kamal_camembert_dummy_nskamal","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kamal_camembert_dummy_nskamal|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/nskamal/kamal_camembert_dummy
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-kamal_camembert_dummy_nskamal_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-kamal_camembert_dummy_nskamal_pipeline_en.md
new file mode 100644
index 00000000000000..a24bde2b7ad4ff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-kamal_camembert_dummy_nskamal_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English kamal_camembert_dummy_nskamal_pipeline pipeline CamemBertEmbeddings from nskamal
+author: John Snow Labs
+name: kamal_camembert_dummy_nskamal_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kamal_camembert_dummy_nskamal_pipeline` is a English model originally trained by nskamal.
+
+{:.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/kamal_camembert_dummy_nskamal_pipeline_en_5.5.0_3.0_1725728726471.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kamal_camembert_dummy_nskamal_pipeline_en_5.5.0_3.0_1725728726471.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
+
+pipeline = PretrainedPipeline("kamal_camembert_dummy_nskamal_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("kamal_camembert_dummy_nskamal_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kamal_camembert_dummy_nskamal_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/nskamal/kamal_camembert_dummy
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-lab1_random_sfliao_en.md b/docs/_posts/ahmedlone127/2024-09-07-lab1_random_sfliao_en.md
new file mode 100644
index 00000000000000..b34218ba321b3f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-lab1_random_sfliao_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English lab1_random_sfliao MarianTransformer from sfliao
+author: John Snow Labs
+name: lab1_random_sfliao
+date: 2024-09-07
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lab1_random_sfliao` is a English model originally trained by sfliao.
+
+{:.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/lab1_random_sfliao_en_5.5.0_3.0_1725746858430.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lab1_random_sfliao_en_5.5.0_3.0_1725746858430.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("lab1_random_sfliao","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("lab1_random_sfliao","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lab1_random_sfliao|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.2 MB|
+
+## References
+
+https://huggingface.co/sfliao/lab1_random
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-lct_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-lct_ner_pipeline_en.md
new file mode 100644
index 00000000000000..29b513a29f0825
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-lct_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English lct_ner_pipeline pipeline DistilBertForTokenClassification from IshikiI-01
+author: John Snow Labs
+name: lct_ner_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lct_ner_pipeline` is a English model originally trained by IshikiI-01.
+
+{:.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/lct_ner_pipeline_en_5.5.0_3.0_1725730274011.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lct_ner_pipeline_en_5.5.0_3.0_1725730274011.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
+
+pipeline = PretrainedPipeline("lct_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lct_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lct_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|666.6 MB|
+
+## References
+
+https://huggingface.co/IshikiI-01/lct_ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-logprecis_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-logprecis_pipeline_en.md
new file mode 100644
index 00000000000000..31f4bd97010790
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-logprecis_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English logprecis_pipeline pipeline RoBertaForTokenClassification from SmartDataPolito
+author: John Snow Labs
+name: logprecis_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`logprecis_pipeline` is a English model originally trained by SmartDataPolito.
+
+{:.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/logprecis_pipeline_en_5.5.0_3.0_1725708353715.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/logprecis_pipeline_en_5.5.0_3.0_1725708353715.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
+
+pipeline = PretrainedPipeline("logprecis_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("logprecis_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|logprecis_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.2 MB|
+
+## References
+
+https://huggingface.co/SmartDataPolito/logprecis
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-mbert_trained_conll2003_english_en.md b/docs/_posts/ahmedlone127/2024-09-07-mbert_trained_conll2003_english_en.md
new file mode 100644
index 00000000000000..eee35e49191554
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-mbert_trained_conll2003_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mbert_trained_conll2003_english DistilBertForTokenClassification from DeepaPeri
+author: John Snow Labs
+name: mbert_trained_conll2003_english
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mbert_trained_conll2003_english` is a English model originally trained by DeepaPeri.
+
+{:.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/mbert_trained_conll2003_english_en_5.5.0_3.0_1725731118375.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mbert_trained_conll2003_english_en_5.5.0_3.0_1725731118375.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("mbert_trained_conll2003_english","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("mbert_trained_conll2003_english", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mbert_trained_conll2003_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/DeepaPeri/MBERT-TRAINED-CONLL2003-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-mbert_trained_conll2003_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-mbert_trained_conll2003_english_pipeline_en.md
new file mode 100644
index 00000000000000..03dd3764a898f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-mbert_trained_conll2003_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mbert_trained_conll2003_english_pipeline pipeline DistilBertForTokenClassification from DeepaPeri
+author: John Snow Labs
+name: mbert_trained_conll2003_english_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mbert_trained_conll2003_english_pipeline` is a English model originally trained by DeepaPeri.
+
+{:.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/mbert_trained_conll2003_english_pipeline_en_5.5.0_3.0_1725731143905.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mbert_trained_conll2003_english_pipeline_en_5.5.0_3.0_1725731143905.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
+
+pipeline = PretrainedPipeline("mbert_trained_conll2003_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mbert_trained_conll2003_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mbert_trained_conll2003_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/DeepaPeri/MBERT-TRAINED-CONLL2003-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-mformer_care_en.md b/docs/_posts/ahmedlone127/2024-09-07-mformer_care_en.md
new file mode 100644
index 00000000000000..c521d5674e2c45
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-mformer_care_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mformer_care RoBertaForSequenceClassification from joshnguyen
+author: John Snow Labs
+name: mformer_care
+date: 2024-09-07
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mformer_care` is a English model originally trained by joshnguyen.
+
+{:.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/mformer_care_en_5.5.0_3.0_1725679884655.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mformer_care_en_5.5.0_3.0_1725679884655.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("mformer_care","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("mformer_care", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mformer_care|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|464.7 MB|
+
+## References
+
+https://huggingface.co/joshnguyen/mformer-care
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-mix_vietnamese_english_4m_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-mix_vietnamese_english_4m_pipeline_en.md
new file mode 100644
index 00000000000000..1b8795238a4cf0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-mix_vietnamese_english_4m_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mix_vietnamese_english_4m_pipeline pipeline MarianTransformer from Eugenememe
+author: John Snow Labs
+name: mix_vietnamese_english_4m_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mix_vietnamese_english_4m_pipeline` is a English model originally trained by Eugenememe.
+
+{:.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/mix_vietnamese_english_4m_pipeline_en_5.5.0_3.0_1725746927463.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mix_vietnamese_english_4m_pipeline_en_5.5.0_3.0_1725746927463.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
+
+pipeline = PretrainedPipeline("mix_vietnamese_english_4m_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mix_vietnamese_english_4m_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mix_vietnamese_english_4m_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|475.7 MB|
+
+## References
+
+https://huggingface.co/Eugenememe/mix-vi-en-4m
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-mmarco_mminilmv2_l12_h384_v1_y2lan_en.md b/docs/_posts/ahmedlone127/2024-09-07-mmarco_mminilmv2_l12_h384_v1_y2lan_en.md
new file mode 100644
index 00000000000000..bd72a2a88b3c73
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-mmarco_mminilmv2_l12_h384_v1_y2lan_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mmarco_mminilmv2_l12_h384_v1_y2lan XlmRoBertaForSequenceClassification from y2lan
+author: John Snow Labs
+name: mmarco_mminilmv2_l12_h384_v1_y2lan
+date: 2024-09-07
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mmarco_mminilmv2_l12_h384_v1_y2lan` is a English model originally trained by y2lan.
+
+{:.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/mmarco_mminilmv2_l12_h384_v1_y2lan_en_5.5.0_3.0_1725671208311.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mmarco_mminilmv2_l12_h384_v1_y2lan_en_5.5.0_3.0_1725671208311.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("mmarco_mminilmv2_l12_h384_v1_y2lan","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("mmarco_mminilmv2_l12_h384_v1_y2lan", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mmarco_mminilmv2_l12_h384_v1_y2lan|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|399.6 MB|
+
+## References
+
+https://huggingface.co/y2lan/mmarco-mMiniLMv2-L12-H384-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-model1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-model1_pipeline_en.md
new file mode 100644
index 00000000000000..cb42b5722c344a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-model1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English model1_pipeline pipeline DistilBertForQuestionAnswering from Vasu07
+author: John Snow Labs
+name: model1_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model1_pipeline` is a English model originally trained by Vasu07.
+
+{:.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/model1_pipeline_en_5.5.0_3.0_1725727004537.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model1_pipeline_en_5.5.0_3.0_1725727004537.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
+
+pipeline = PretrainedPipeline("model1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("model1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Vasu07/model1
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-model3e_norwegian_wd_norwegian_perturb_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-model3e_norwegian_wd_norwegian_perturb_pipeline_en.md
new file mode 100644
index 00000000000000..fd0658f616a4f9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-model3e_norwegian_wd_norwegian_perturb_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English model3e_norwegian_wd_norwegian_perturb_pipeline pipeline DistilBertForTokenClassification from cria111
+author: John Snow Labs
+name: model3e_norwegian_wd_norwegian_perturb_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model3e_norwegian_wd_norwegian_perturb_pipeline` is a English model originally trained by cria111.
+
+{:.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/model3e_norwegian_wd_norwegian_perturb_pipeline_en_5.5.0_3.0_1725739679180.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model3e_norwegian_wd_norwegian_perturb_pipeline_en_5.5.0_3.0_1725739679180.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
+
+pipeline = PretrainedPipeline("model3e_norwegian_wd_norwegian_perturb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("model3e_norwegian_wd_norwegian_perturb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model3e_norwegian_wd_norwegian_perturb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/cria111/model3e_no_wd_no_perturb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-model_name_kayyyy27_en.md b/docs/_posts/ahmedlone127/2024-09-07-model_name_kayyyy27_en.md
new file mode 100644
index 00000000000000..e47eb6615f7476
--- /dev/null
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@@ -0,0 +1,94 @@
+---
+layout: model
+title: English model_name_kayyyy27 DistilBertForSequenceClassification from Kayyyy27
+author: John Snow Labs
+name: model_name_kayyyy27
+date: 2024-09-07
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_name_kayyyy27` is a English model originally trained by Kayyyy27.
+
+{:.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/model_name_kayyyy27_en_5.5.0_3.0_1725674438723.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_name_kayyyy27_en_5.5.0_3.0_1725674438723.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("model_name_kayyyy27","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("model_name_kayyyy27", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_name_kayyyy27|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Kayyyy27/model_name
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-model_vrushali_en.md b/docs/_posts/ahmedlone127/2024-09-07-model_vrushali_en.md
new file mode 100644
index 00000000000000..8e5e45dcfbd2d3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-model_vrushali_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English model_vrushali DistilBertForTokenClassification from Vrushali
+author: John Snow Labs
+name: model_vrushali
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_vrushali` is a English model originally trained by Vrushali.
+
+{:.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/model_vrushali_en_5.5.0_3.0_1725739591550.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_vrushali_en_5.5.0_3.0_1725739591550.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("model_vrushali","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("model_vrushali", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_vrushali|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Vrushali/model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-n_roberta_imdb_padding60model_en.md b/docs/_posts/ahmedlone127/2024-09-07-n_roberta_imdb_padding60model_en.md
new file mode 100644
index 00000000000000..7c4c081f416035
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-n_roberta_imdb_padding60model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English n_roberta_imdb_padding60model RoBertaForSequenceClassification from Realgon
+author: John Snow Labs
+name: n_roberta_imdb_padding60model
+date: 2024-09-07
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`n_roberta_imdb_padding60model` is a English model originally trained by Realgon.
+
+{:.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/n_roberta_imdb_padding60model_en_5.5.0_3.0_1725680453834.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/n_roberta_imdb_padding60model_en_5.5.0_3.0_1725680453834.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("n_roberta_imdb_padding60model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("n_roberta_imdb_padding60model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|n_roberta_imdb_padding60model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|463.2 MB|
+
+## References
+
+https://huggingface.co/Realgon/N_roberta_imdb_padding60model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-nepal_bhasa_trained_danish_en.md b/docs/_posts/ahmedlone127/2024-09-07-nepal_bhasa_trained_danish_en.md
new file mode 100644
index 00000000000000..45cb5fc9d00767
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-nepal_bhasa_trained_danish_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English nepal_bhasa_trained_danish DistilBertForTokenClassification from annamariagnat
+author: John Snow Labs
+name: nepal_bhasa_trained_danish
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nepal_bhasa_trained_danish` is a English model originally trained by annamariagnat.
+
+{:.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/nepal_bhasa_trained_danish_en_5.5.0_3.0_1725729759011.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nepal_bhasa_trained_danish_en_5.5.0_3.0_1725729759011.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("nepal_bhasa_trained_danish","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("nepal_bhasa_trained_danish", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nepal_bhasa_trained_danish|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/annamariagnat/NEW_trained_danish
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-ner_cw_pipeline_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-ner_cw_pipeline_pipeline_en.md
new file mode 100644
index 00000000000000..0da01b1f74af9a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-ner_cw_pipeline_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_cw_pipeline_pipeline pipeline DistilBertForTokenClassification from ArshiaKarimian
+author: John Snow Labs
+name: ner_cw_pipeline_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_cw_pipeline_pipeline` is a English model originally trained by ArshiaKarimian.
+
+{:.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/ner_cw_pipeline_pipeline_en_5.5.0_3.0_1725729798955.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_cw_pipeline_pipeline_en_5.5.0_3.0_1725729798955.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
+
+pipeline = PretrainedPipeline("ner_cw_pipeline_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_cw_pipeline_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_cw_pipeline_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/ArshiaKarimian/NER_CW_pipeline
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-ner_legal_german_de.md b/docs/_posts/ahmedlone127/2024-09-07-ner_legal_german_de.md
new file mode 100644
index 00000000000000..1baf8ed0ab2261
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-ner_legal_german_de.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: German ner_legal_german BertForTokenClassification from Sahajtomar
+author: John Snow Labs
+name: ner_legal_german
+date: 2024-09-07
+tags: [de, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_legal_german` is a German model originally trained by Sahajtomar.
+
+{:.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/ner_legal_german_de_5.5.0_3.0_1725726220672.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_legal_german_de_5.5.0_3.0_1725726220672.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("ner_legal_german","de") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("ner_legal_german", "de")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_legal_german|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|de|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Sahajtomar/NER_legal_de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-ner_model_arshiakarimian_en.md b/docs/_posts/ahmedlone127/2024-09-07-ner_model_arshiakarimian_en.md
new file mode 100644
index 00000000000000..a56ad3d73398ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-ner_model_arshiakarimian_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_model_arshiakarimian DistilBertForTokenClassification from ArshiaKarimian
+author: John Snow Labs
+name: ner_model_arshiakarimian
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_model_arshiakarimian` is a English model originally trained by ArshiaKarimian.
+
+{:.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/ner_model_arshiakarimian_en_5.5.0_3.0_1725739470293.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_model_arshiakarimian_en_5.5.0_3.0_1725739470293.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("ner_model_arshiakarimian","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("ner_model_arshiakarimian", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_model_arshiakarimian|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/ArshiaKarimian/NER_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-ner_model_ep2_en.md b/docs/_posts/ahmedlone127/2024-09-07-ner_model_ep2_en.md
new file mode 100644
index 00000000000000..9a96bb4dde6cef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-ner_model_ep2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_model_ep2 DistilBertForTokenClassification from Polo123
+author: John Snow Labs
+name: ner_model_ep2
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_model_ep2` is a English model originally trained by Polo123.
+
+{:.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/ner_model_ep2_en_5.5.0_3.0_1725739166420.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_model_ep2_en_5.5.0_3.0_1725739166420.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("ner_model_ep2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("ner_model_ep2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_model_ep2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Polo123/ner_model_ep2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-ner_model_ep2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-ner_model_ep2_pipeline_en.md
new file mode 100644
index 00000000000000..53ee02595bb305
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-ner_model_ep2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_model_ep2_pipeline pipeline DistilBertForTokenClassification from Polo123
+author: John Snow Labs
+name: ner_model_ep2_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_model_ep2_pipeline` is a English model originally trained by Polo123.
+
+{:.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/ner_model_ep2_pipeline_en_5.5.0_3.0_1725739178275.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_model_ep2_pipeline_en_5.5.0_3.0_1725739178275.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
+
+pipeline = PretrainedPipeline("ner_model_ep2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_model_ep2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_model_ep2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Polo123/ner_model_ep2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-ner_twitter_fine_tune_en.md b/docs/_posts/ahmedlone127/2024-09-07-ner_twitter_fine_tune_en.md
new file mode 100644
index 00000000000000..e0837bdf487f0c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-ner_twitter_fine_tune_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_twitter_fine_tune DistilBertForTokenClassification from chenxu0602
+author: John Snow Labs
+name: ner_twitter_fine_tune
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_twitter_fine_tune` is a English model originally trained by chenxu0602.
+
+{:.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/ner_twitter_fine_tune_en_5.5.0_3.0_1725730960736.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_twitter_fine_tune_en_5.5.0_3.0_1725730960736.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("ner_twitter_fine_tune","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("ner_twitter_fine_tune", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_twitter_fine_tune|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/chenxu0602/ner_twitter_fine_tune
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-nlp_question_answering_hw_en.md b/docs/_posts/ahmedlone127/2024-09-07-nlp_question_answering_hw_en.md
new file mode 100644
index 00000000000000..566b748232c5e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-nlp_question_answering_hw_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English nlp_question_answering_hw DistilBertForQuestionAnswering from iMahdiGhazavi
+author: John Snow Labs
+name: nlp_question_answering_hw
+date: 2024-09-07
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_question_answering_hw` is a English model originally trained by iMahdiGhazavi.
+
+{:.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/nlp_question_answering_hw_en_5.5.0_3.0_1725722585990.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_question_answering_hw_en_5.5.0_3.0_1725722585990.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("nlp_question_answering_hw","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("nlp_question_answering_hw", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nlp_question_answering_hw|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/iMahdiGhazavi/nlp-question-answering-hw
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-norwegian_bokml_bert_base_pipeline_no.md b/docs/_posts/ahmedlone127/2024-09-07-norwegian_bokml_bert_base_pipeline_no.md
new file mode 100644
index 00000000000000..9fe0f079672bd3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-norwegian_bokml_bert_base_pipeline_no.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Norwegian norwegian_bokml_bert_base_pipeline pipeline BertEmbeddings from NbAiLab
+author: John Snow Labs
+name: norwegian_bokml_bert_base_pipeline
+date: 2024-09-07
+tags: ["no", open_source, pipeline, onnx]
+task: Embeddings
+language: "no"
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norwegian_bokml_bert_base_pipeline` is a Norwegian model originally trained by NbAiLab.
+
+{:.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/norwegian_bokml_bert_base_pipeline_no_5.5.0_3.0_1725697141625.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norwegian_bokml_bert_base_pipeline_no_5.5.0_3.0_1725697141625.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
+
+pipeline = PretrainedPipeline("norwegian_bokml_bert_base_pipeline", lang = "no")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("norwegian_bokml_bert_base_pipeline", lang = "no")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|norwegian_bokml_bert_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|no|
+|Size:|666.2 MB|
+
+## References
+
+https://huggingface.co/NbAiLab/nb-bert-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-nsfw_prompt_detector_en.md b/docs/_posts/ahmedlone127/2024-09-07-nsfw_prompt_detector_en.md
new file mode 100644
index 00000000000000..aa793ec512b721
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-nsfw_prompt_detector_en.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: English nsfw_prompt_detector DistilBertForSequenceClassification from Zlatislav
+author: John Snow Labs
+name: nsfw_prompt_detector
+date: 2024-09-07
+tags: [bert, en, open_source, sequence_classification, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nsfw_prompt_detector` is a English model originally trained by Zlatislav.
+
+## 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/nsfw_prompt_detector_en_5.5.0_3.0_1725675133058.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nsfw_prompt_detector_en_5.5.0_3.0_1725675133058.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("document")
+
+tokenizer = Tokenizer()\
+    .setInputCols("document")\
+    .setOutputCol("token")  
+    
+sequenceClassifier = DistilBertForSequenceClassification.pretrained("nsfw_prompt_detector","en")\
+            .setInputCols(["document","token"])\
+            .setOutputCol("class")
+
+pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text")
+    .setOutputCol("document")
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document") 
+    .setOutputCol("token")  
+    
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("nsfw_prompt_detector","en")
+            .setInputCols(Array("document","token"))
+            .setOutputCol("class")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nsfw_prompt_detector|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+References
+
+https://huggingface.co/Zlatislav/NSFW-Prompt-Detector
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-opendispatcher_v3_gpt35turbo_and_gpt4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-opendispatcher_v3_gpt35turbo_and_gpt4_pipeline_en.md
new file mode 100644
index 00000000000000..1f51c32172ce47
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-opendispatcher_v3_gpt35turbo_and_gpt4_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opendispatcher_v3_gpt35turbo_and_gpt4_pipeline pipeline DistilBertForSequenceClassification from gaodrew
+author: John Snow Labs
+name: opendispatcher_v3_gpt35turbo_and_gpt4_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opendispatcher_v3_gpt35turbo_and_gpt4_pipeline` is a English model originally trained by gaodrew.
+
+{:.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/opendispatcher_v3_gpt35turbo_and_gpt4_pipeline_en_5.5.0_3.0_1725674783428.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opendispatcher_v3_gpt35turbo_and_gpt4_pipeline_en_5.5.0_3.0_1725674783428.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
+
+pipeline = PretrainedPipeline("opendispatcher_v3_gpt35turbo_and_gpt4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opendispatcher_v3_gpt35turbo_and_gpt4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opendispatcher_v3_gpt35turbo_and_gpt4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/gaodrew/OpenDispatcher_v3_gpt35turbo_and_gpt4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_2000instances_un_multi_leaningrate2e_05_batchsize8_11_action_1_en.md b/docs/_posts/ahmedlone127/2024-09-07-opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_2000instances_un_multi_leaningrate2e_05_batchsize8_11_action_1_en.md
new file mode 100644
index 00000000000000..a6b35f54d3babc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_2000instances_un_multi_leaningrate2e_05_batchsize8_11_action_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_2000instances_un_multi_leaningrate2e_05_batchsize8_11_action_1 MarianTransformer from meghazisofiane
+author: John Snow Labs
+name: opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_2000instances_un_multi_leaningrate2e_05_batchsize8_11_action_1
+date: 2024-09-07
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_2000instances_un_multi_leaningrate2e_05_batchsize8_11_action_1` is a English model originally trained by meghazisofiane.
+
+{:.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/opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_2000instances_un_multi_leaningrate2e_05_batchsize8_11_action_1_en_5.5.0_3.0_1725746745015.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_2000instances_un_multi_leaningrate2e_05_batchsize8_11_action_1_en_5.5.0_3.0_1725746745015.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_2000instances_un_multi_leaningrate2e_05_batchsize8_11_action_1","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_2000instances_un_multi_leaningrate2e_05_batchsize8_11_action_1","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_2000instances_un_multi_leaningrate2e_05_batchsize8_11_action_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|528.2 MB|
+
+## References
+
+https://huggingface.co/meghazisofiane/opus-mt-en-ar-evaluated-en-to-ar-2000instances-un_multi-leaningRate2e-05-batchSize8-11-action-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_karunac_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_karunac_pipeline_en.md
new file mode 100644
index 00000000000000..00d881d6d7c8ae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_karunac_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_karunac_pipeline pipeline MarianTransformer from karunac
+author: John Snow Labs
+name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_karunac_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_karunac_pipeline` is a English model originally trained by karunac.
+
+{:.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/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_karunac_pipeline_en_5.5.0_3.0_1725748010313.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_karunac_pipeline_en_5.5.0_3.0_1725748010313.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
+
+pipeline = PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_karunac_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_karunac_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_karunac_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|509.2 MB|
+
+## References
+
+https://huggingface.co/karunac/opus-mt-en-ro-finetuned-en-to-ro
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_likhith231_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_likhith231_pipeline_en.md
new file mode 100644
index 00000000000000..10f3bed00ab259
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_likhith231_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_likhith231_pipeline pipeline MarianTransformer from likhith231
+author: John Snow Labs
+name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_likhith231_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_likhith231_pipeline` is a English model originally trained by likhith231.
+
+{:.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/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_likhith231_pipeline_en_5.5.0_3.0_1725741097896.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_likhith231_pipeline_en_5.5.0_3.0_1725741097896.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
+
+pipeline = PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_likhith231_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_likhith231_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_likhith231_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|509.0 MB|
+
+## References
+
+https://huggingface.co/likhith231/opus-mt-en-ro-finetuned-en-to-ro
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-opus_maltese_english_romanian_finetuned_romanian_tonga_tonga_islands_english_clean_marianmt_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-opus_maltese_english_romanian_finetuned_romanian_tonga_tonga_islands_english_clean_marianmt_pipeline_en.md
new file mode 100644
index 00000000000000..0d92e549baa176
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-opus_maltese_english_romanian_finetuned_romanian_tonga_tonga_islands_english_clean_marianmt_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_romanian_finetuned_romanian_tonga_tonga_islands_english_clean_marianmt_pipeline pipeline MarianTransformer from himanshubeniwal
+author: John Snow Labs
+name: opus_maltese_english_romanian_finetuned_romanian_tonga_tonga_islands_english_clean_marianmt_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_romanian_tonga_tonga_islands_english_clean_marianmt_pipeline` is a English model originally trained by himanshubeniwal.
+
+{:.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/opus_maltese_english_romanian_finetuned_romanian_tonga_tonga_islands_english_clean_marianmt_pipeline_en_5.5.0_3.0_1725740592917.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_romanian_tonga_tonga_islands_english_clean_marianmt_pipeline_en_5.5.0_3.0_1725740592917.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
+
+pipeline = PretrainedPipeline("opus_maltese_english_romanian_finetuned_romanian_tonga_tonga_islands_english_clean_marianmt_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_romanian_finetuned_romanian_tonga_tonga_islands_english_clean_marianmt_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_romanian_finetuned_romanian_tonga_tonga_islands_english_clean_marianmt_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|508.5 MB|
+
+## References
+
+https://huggingface.co/himanshubeniwal/opus-mt-en-ro-finetuned-ro-to-en-clean-MarianMT
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-opus_maltese_ganda_english_finetuned_lm_tonga_tonga_islands_english_en.md b/docs/_posts/ahmedlone127/2024-09-07-opus_maltese_ganda_english_finetuned_lm_tonga_tonga_islands_english_en.md
new file mode 100644
index 00000000000000..dfffb6f17acff7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-opus_maltese_ganda_english_finetuned_lm_tonga_tonga_islands_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_ganda_english_finetuned_lm_tonga_tonga_islands_english MarianTransformer from Eyesiga
+author: John Snow Labs
+name: opus_maltese_ganda_english_finetuned_lm_tonga_tonga_islands_english
+date: 2024-09-07
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_ganda_english_finetuned_lm_tonga_tonga_islands_english` is a English model originally trained by Eyesiga.
+
+{:.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/opus_maltese_ganda_english_finetuned_lm_tonga_tonga_islands_english_en_5.5.0_3.0_1725740626800.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_ganda_english_finetuned_lm_tonga_tonga_islands_english_en_5.5.0_3.0_1725740626800.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_ganda_english_finetuned_lm_tonga_tonga_islands_english","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_ganda_english_finetuned_lm_tonga_tonga_islands_english","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_ganda_english_finetuned_lm_tonga_tonga_islands_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|511.9 MB|
+
+## References
+
+https://huggingface.co/Eyesiga/opus-mt-lg-en-finetuned-lm-to-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_donghyunkim_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_donghyunkim_pipeline_en.md
new file mode 100644
index 00000000000000..d3640fdd1ceb93
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_donghyunkim_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_donghyunkim_pipeline pipeline MarianTransformer from DongHyunKim
+author: John Snow Labs
+name: opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_donghyunkim_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_donghyunkim_pipeline` is a English model originally trained by DongHyunKim.
+
+{:.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/opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_donghyunkim_pipeline_en_5.5.0_3.0_1725741707168.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_donghyunkim_pipeline_en_5.5.0_3.0_1725741707168.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
+
+pipeline = PretrainedPipeline("opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_donghyunkim_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_donghyunkim_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_donghyunkim_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|500.1 MB|
+
+## References
+
+https://huggingface.co/DongHyunKim/opus-mt-de-en-finetuned-de-to-en
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_second_felipetanios_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_second_felipetanios_pipeline_en.md
new file mode 100644
index 00000000000000..5afa6f0a316291
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_second_felipetanios_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_second_felipetanios_pipeline pipeline MarianTransformer from felipetanios
+author: John Snow Labs
+name: opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_second_felipetanios_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_second_felipetanios_pipeline` is a English model originally trained by felipetanios.
+
+{:.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/opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_second_felipetanios_pipeline_en_5.5.0_3.0_1725748123359.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_second_felipetanios_pipeline_en_5.5.0_3.0_1725748123359.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
+
+pipeline = PretrainedPipeline("opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_second_felipetanios_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_second_felipetanios_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_german_english_finetuned_german_tonga_tonga_islands_english_second_felipetanios_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|499.9 MB|
+
+## References
+
+https://huggingface.co/felipetanios/opus-mt-de-en-finetuned-de-to-en-second
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-opus_maltese_italian_english_finetuned_5000_italian_tonga_tonga_islands_english_en.md b/docs/_posts/ahmedlone127/2024-09-07-opus_maltese_italian_english_finetuned_5000_italian_tonga_tonga_islands_english_en.md
new file mode 100644
index 00000000000000..61280672384b8a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-opus_maltese_italian_english_finetuned_5000_italian_tonga_tonga_islands_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_italian_english_finetuned_5000_italian_tonga_tonga_islands_english MarianTransformer from VFiona
+author: John Snow Labs
+name: opus_maltese_italian_english_finetuned_5000_italian_tonga_tonga_islands_english
+date: 2024-09-07
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_italian_english_finetuned_5000_italian_tonga_tonga_islands_english` is a English model originally trained by VFiona.
+
+{:.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/opus_maltese_italian_english_finetuned_5000_italian_tonga_tonga_islands_english_en_5.5.0_3.0_1725746526692.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_italian_english_finetuned_5000_italian_tonga_tonga_islands_english_en_5.5.0_3.0_1725746526692.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_italian_english_finetuned_5000_italian_tonga_tonga_islands_english","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_italian_english_finetuned_5000_italian_tonga_tonga_islands_english","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_italian_english_finetuned_5000_italian_tonga_tonga_islands_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|624.9 MB|
+
+## References
+
+https://huggingface.co/VFiona/opus-mt-it-en-finetuned_5000-it-to-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-opus_maltese_romance_english_finetuned_npomo_english_15_epochs_en.md b/docs/_posts/ahmedlone127/2024-09-07-opus_maltese_romance_english_finetuned_npomo_english_15_epochs_en.md
new file mode 100644
index 00000000000000..f7ce0b82d3cc67
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-opus_maltese_romance_english_finetuned_npomo_english_15_epochs_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_romance_english_finetuned_npomo_english_15_epochs MarianTransformer from UnassumingOwl
+author: John Snow Labs
+name: opus_maltese_romance_english_finetuned_npomo_english_15_epochs
+date: 2024-09-07
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_romance_english_finetuned_npomo_english_15_epochs` is a English model originally trained by UnassumingOwl.
+
+{:.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/opus_maltese_romance_english_finetuned_npomo_english_15_epochs_en_5.5.0_3.0_1725746894598.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_romance_english_finetuned_npomo_english_15_epochs_en_5.5.0_3.0_1725746894598.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_romance_english_finetuned_npomo_english_15_epochs","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_romance_english_finetuned_npomo_english_15_epochs","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_romance_english_finetuned_npomo_english_15_epochs|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|538.9 MB|
+
+## References
+
+https://huggingface.co/UnassumingOwl/opus-mt-ROMANCE-en-finetuned-npomo-en-15-epochs
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-opus_maltese_tc_big_english_arabic_finetuned_franco_tonga_tonga_islands_arabic_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-opus_maltese_tc_big_english_arabic_finetuned_franco_tonga_tonga_islands_arabic_2_pipeline_en.md
new file mode 100644
index 00000000000000..0741b59f48e5d0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-opus_maltese_tc_big_english_arabic_finetuned_franco_tonga_tonga_islands_arabic_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_tc_big_english_arabic_finetuned_franco_tonga_tonga_islands_arabic_2_pipeline pipeline MarianTransformer from mohamedtolba
+author: John Snow Labs
+name: opus_maltese_tc_big_english_arabic_finetuned_franco_tonga_tonga_islands_arabic_2_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_tc_big_english_arabic_finetuned_franco_tonga_tonga_islands_arabic_2_pipeline` is a English model originally trained by mohamedtolba.
+
+{:.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/opus_maltese_tc_big_english_arabic_finetuned_franco_tonga_tonga_islands_arabic_2_pipeline_en_5.5.0_3.0_1725747905491.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_tc_big_english_arabic_finetuned_franco_tonga_tonga_islands_arabic_2_pipeline_en_5.5.0_3.0_1725747905491.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
+
+pipeline = PretrainedPipeline("opus_maltese_tc_big_english_arabic_finetuned_franco_tonga_tonga_islands_arabic_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_tc_big_english_arabic_finetuned_franco_tonga_tonga_islands_arabic_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_tc_big_english_arabic_finetuned_franco_tonga_tonga_islands_arabic_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/mohamedtolba/opus-mt-tc-big-en-ar-finetuned-franco-to-arabic-2
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-parsbert_persian_qa_fa.md b/docs/_posts/ahmedlone127/2024-09-07-parsbert_persian_qa_fa.md
new file mode 100644
index 00000000000000..a119b20737fbe3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-parsbert_persian_qa_fa.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Persian parsbert_persian_qa BertForQuestionAnswering from mansoorhamidzadeh
+author: John Snow Labs
+name: parsbert_persian_qa
+date: 2024-09-07
+tags: [fa, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: fa
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`parsbert_persian_qa` is a Persian model originally trained by mansoorhamidzadeh.
+
+{:.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/parsbert_persian_qa_fa_5.5.0_3.0_1725709116722.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/parsbert_persian_qa_fa_5.5.0_3.0_1725709116722.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("parsbert_persian_qa","fa") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("parsbert_persian_qa", "fa")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|parsbert_persian_qa|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|fa|
+|Size:|441.6 MB|
+
+## References
+
+https://huggingface.co/mansoorhamidzadeh/parsbert-persian-QA
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-pii_distilbert_v3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-pii_distilbert_v3_pipeline_en.md
new file mode 100644
index 00000000000000..cb9205c9ef3801
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-pii_distilbert_v3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English pii_distilbert_v3_pipeline pipeline DistilBertForTokenClassification from giji2
+author: John Snow Labs
+name: pii_distilbert_v3_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pii_distilbert_v3_pipeline` is a English model originally trained by giji2.
+
+{:.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/pii_distilbert_v3_pipeline_en_5.5.0_3.0_1725730874952.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pii_distilbert_v3_pipeline_en_5.5.0_3.0_1725730874952.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
+
+pipeline = PretrainedPipeline("pii_distilbert_v3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("pii_distilbert_v3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pii_distilbert_v3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/giji2/pii_distilbert_v3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-pii_model_based_on_distilbert_en.md b/docs/_posts/ahmedlone127/2024-09-07-pii_model_based_on_distilbert_en.md
new file mode 100644
index 00000000000000..033941c378a2ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-pii_model_based_on_distilbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English pii_model_based_on_distilbert DistilBertForTokenClassification from ab-ai
+author: John Snow Labs
+name: pii_model_based_on_distilbert
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pii_model_based_on_distilbert` is a English model originally trained by ab-ai.
+
+{:.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/pii_model_based_on_distilbert_en_5.5.0_3.0_1725734107418.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pii_model_based_on_distilbert_en_5.5.0_3.0_1725734107418.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("pii_model_based_on_distilbert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("pii_model_based_on_distilbert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pii_model_based_on_distilbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.4 MB|
+
+## References
+
+https://huggingface.co/ab-ai/pii_model_based_on_distilbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-portuguese_finegrained_one_shot_en.md b/docs/_posts/ahmedlone127/2024-09-07-portuguese_finegrained_one_shot_en.md
new file mode 100644
index 00000000000000..6f7fc946ebf504
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-portuguese_finegrained_one_shot_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English portuguese_finegrained_one_shot XlmRoBertaForSequenceClassification from edwardgowsmith
+author: John Snow Labs
+name: portuguese_finegrained_one_shot
+date: 2024-09-07
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`portuguese_finegrained_one_shot` is a English model originally trained by edwardgowsmith.
+
+{:.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/portuguese_finegrained_one_shot_en_5.5.0_3.0_1725713257691.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/portuguese_finegrained_one_shot_en_5.5.0_3.0_1725713257691.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("portuguese_finegrained_one_shot","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("portuguese_finegrained_one_shot", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|portuguese_finegrained_one_shot|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|782.9 MB|
+
+## References
+
+https://huggingface.co/edwardgowsmith/pt-finegrained-one-shot
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-pubchem10m_smiles_bpe_390k_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-pubchem10m_smiles_bpe_390k_pipeline_en.md
new file mode 100644
index 00000000000000..071243293f5b33
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-pubchem10m_smiles_bpe_390k_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English pubchem10m_smiles_bpe_390k_pipeline pipeline RoBertaEmbeddings from seyonec
+author: John Snow Labs
+name: pubchem10m_smiles_bpe_390k_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pubchem10m_smiles_bpe_390k_pipeline` is a English model originally trained by seyonec.
+
+{:.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/pubchem10m_smiles_bpe_390k_pipeline_en_5.5.0_3.0_1725716005973.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pubchem10m_smiles_bpe_390k_pipeline_en_5.5.0_3.0_1725716005973.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
+
+pipeline = PretrainedPipeline("pubchem10m_smiles_bpe_390k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("pubchem10m_smiles_bpe_390k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|pubchem10m_smiles_bpe_390k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|311.0 MB|
+
+## References
+
+https://huggingface.co/seyonec/PubChem10M_SMILES_BPE_390k
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-qa2_iiitdmj_testing_en.md b/docs/_posts/ahmedlone127/2024-09-07-qa2_iiitdmj_testing_en.md
new file mode 100644
index 00000000000000..396d6a7d146b05
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-qa2_iiitdmj_testing_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English qa2_iiitdmj_testing DistilBertForQuestionAnswering from samhitmantrala
+author: John Snow Labs
+name: qa2_iiitdmj_testing
+date: 2024-09-07
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa2_iiitdmj_testing` is a English model originally trained by samhitmantrala.
+
+{:.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/qa2_iiitdmj_testing_en_5.5.0_3.0_1725722308097.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa2_iiitdmj_testing_en_5.5.0_3.0_1725722308097.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("qa2_iiitdmj_testing","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("qa2_iiitdmj_testing", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa2_iiitdmj_testing|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/samhitmantrala/qa2_iiitdmj_testing
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-qa2_iiitdmj_testing_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-qa2_iiitdmj_testing_pipeline_en.md
new file mode 100644
index 00000000000000..ca54c2b9bcfa81
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-qa2_iiitdmj_testing_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qa2_iiitdmj_testing_pipeline pipeline DistilBertForQuestionAnswering from samhitmantrala
+author: John Snow Labs
+name: qa2_iiitdmj_testing_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa2_iiitdmj_testing_pipeline` is a English model originally trained by samhitmantrala.
+
+{:.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/qa2_iiitdmj_testing_pipeline_en_5.5.0_3.0_1725722322619.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa2_iiitdmj_testing_pipeline_en_5.5.0_3.0_1725722322619.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
+
+pipeline = PretrainedPipeline("qa2_iiitdmj_testing_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qa2_iiitdmj_testing_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa2_iiitdmj_testing_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/samhitmantrala/qa2_iiitdmj_testing
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-qa_distilbert_matovu_ronald_en.md b/docs/_posts/ahmedlone127/2024-09-07-qa_distilbert_matovu_ronald_en.md
new file mode 100644
index 00000000000000..c1840943d5d95a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-qa_distilbert_matovu_ronald_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English qa_distilbert_matovu_ronald DistilBertForQuestionAnswering from matovu-ronald
+author: John Snow Labs
+name: qa_distilbert_matovu_ronald
+date: 2024-09-07
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_distilbert_matovu_ronald` is a English model originally trained by matovu-ronald.
+
+{:.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/qa_distilbert_matovu_ronald_en_5.5.0_3.0_1725727189712.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_distilbert_matovu_ronald_en_5.5.0_3.0_1725727189712.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("qa_distilbert_matovu_ronald","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("qa_distilbert_matovu_ronald", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_distilbert_matovu_ronald|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/matovu-ronald/qa_distilbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-qa_iiitdmj_testing_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-qa_iiitdmj_testing_pipeline_en.md
new file mode 100644
index 00000000000000..7a1b5e1530542a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-qa_iiitdmj_testing_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qa_iiitdmj_testing_pipeline pipeline DistilBertForQuestionAnswering from samhitmantrala
+author: John Snow Labs
+name: qa_iiitdmj_testing_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_iiitdmj_testing_pipeline` is a English model originally trained by samhitmantrala.
+
+{:.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/qa_iiitdmj_testing_pipeline_en_5.5.0_3.0_1725727582677.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_iiitdmj_testing_pipeline_en_5.5.0_3.0_1725727582677.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
+
+pipeline = PretrainedPipeline("qa_iiitdmj_testing_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qa_iiitdmj_testing_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_iiitdmj_testing_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/samhitmantrala/qa_iiitdmj_testing
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-qa_model_small_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-qa_model_small_pipeline_en.md
new file mode 100644
index 00000000000000..3e11e4b7a3bda9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-qa_model_small_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qa_model_small_pipeline pipeline DistilBertForQuestionAnswering from zhaoxinwind
+author: John Snow Labs
+name: qa_model_small_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_model_small_pipeline` is a English model originally trained by zhaoxinwind.
+
+{:.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/qa_model_small_pipeline_en_5.5.0_3.0_1725722680478.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_model_small_pipeline_en_5.5.0_3.0_1725722680478.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
+
+pipeline = PretrainedPipeline("qa_model_small_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qa_model_small_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_model_small_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/zhaoxinwind/QA_model_small
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-qa_model_study_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-qa_model_study_1_pipeline_en.md
new file mode 100644
index 00000000000000..7ba1d47889e050
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-qa_model_study_1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qa_model_study_1_pipeline pipeline DistilBertForQuestionAnswering from konstaya
+author: John Snow Labs
+name: qa_model_study_1_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_model_study_1_pipeline` is a English model originally trained by konstaya.
+
+{:.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/qa_model_study_1_pipeline_en_5.5.0_3.0_1725735730153.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_model_study_1_pipeline_en_5.5.0_3.0_1725735730153.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
+
+pipeline = PretrainedPipeline("qa_model_study_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qa_model_study_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_model_study_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/konstaya/qa_model_study_1
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-r_t_sms_lm_en.md b/docs/_posts/ahmedlone127/2024-09-07-r_t_sms_lm_en.md
new file mode 100644
index 00000000000000..d82f570d45ef8e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-r_t_sms_lm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English r_t_sms_lm RoBertaEmbeddings from adnankhawaja
+author: John Snow Labs
+name: r_t_sms_lm
+date: 2024-09-07
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`r_t_sms_lm` is a English model originally trained by adnankhawaja.
+
+{:.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/r_t_sms_lm_en_5.5.0_3.0_1725716790372.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/r_t_sms_lm_en_5.5.0_3.0_1725716790372.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("r_t_sms_lm","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("r_t_sms_lm","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|r_t_sms_lm|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|465.9 MB|
+
+## References
+
+https://huggingface.co/adnankhawaja/R_T_SMS_LM
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-random_initialization_kde4_english_tonga_tonga_islands_french_en.md b/docs/_posts/ahmedlone127/2024-09-07-random_initialization_kde4_english_tonga_tonga_islands_french_en.md
new file mode 100644
index 00000000000000..2f79fde11b4103
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-random_initialization_kde4_english_tonga_tonga_islands_french_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English random_initialization_kde4_english_tonga_tonga_islands_french MarianTransformer from C-n
+author: John Snow Labs
+name: random_initialization_kde4_english_tonga_tonga_islands_french
+date: 2024-09-07
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`random_initialization_kde4_english_tonga_tonga_islands_french` is a English model originally trained by C-n.
+
+{:.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/random_initialization_kde4_english_tonga_tonga_islands_french_en_5.5.0_3.0_1725747165039.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/random_initialization_kde4_english_tonga_tonga_islands_french_en_5.5.0_3.0_1725747165039.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("random_initialization_kde4_english_tonga_tonga_islands_french","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("random_initialization_kde4_english_tonga_tonga_islands_french","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|random_initialization_kde4_english_tonga_tonga_islands_french|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|510.2 MB|
+
+## References
+
+https://huggingface.co/C-n/random-initialization-kde4-en-to-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-random_initialization_kde4_english_tonga_tonga_islands_french_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-random_initialization_kde4_english_tonga_tonga_islands_french_pipeline_en.md
new file mode 100644
index 00000000000000..6edfabd19b9ded
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-random_initialization_kde4_english_tonga_tonga_islands_french_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English random_initialization_kde4_english_tonga_tonga_islands_french_pipeline pipeline MarianTransformer from C-n
+author: John Snow Labs
+name: random_initialization_kde4_english_tonga_tonga_islands_french_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`random_initialization_kde4_english_tonga_tonga_islands_french_pipeline` is a English model originally trained by C-n.
+
+{:.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/random_initialization_kde4_english_tonga_tonga_islands_french_pipeline_en_5.5.0_3.0_1725747188926.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/random_initialization_kde4_english_tonga_tonga_islands_french_pipeline_en_5.5.0_3.0_1725747188926.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
+
+pipeline = PretrainedPipeline("random_initialization_kde4_english_tonga_tonga_islands_french_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("random_initialization_kde4_english_tonga_tonga_islands_french_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|random_initialization_kde4_english_tonga_tonga_islands_french_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|510.7 MB|
+
+## References
+
+https://huggingface.co/C-n/random-initialization-kde4-en-to-fr
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-results_elseif02_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-results_elseif02_pipeline_en.md
new file mode 100644
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--- /dev/null
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@@ -0,0 +1,69 @@
+---
+layout: model
+title: English results_elseif02_pipeline pipeline DistilBertForQuestionAnswering from Elseif02
+author: John Snow Labs
+name: results_elseif02_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_elseif02_pipeline` is a English model originally trained by Elseif02.
+
+{:.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/results_elseif02_pipeline_en_5.5.0_3.0_1725722691433.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_elseif02_pipeline_en_5.5.0_3.0_1725722691433.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
+
+pipeline = PretrainedPipeline("results_elseif02_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("results_elseif02_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_elseif02_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/Elseif02/results
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-rg_clean_signatures_southern_sotho_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-rg_clean_signatures_southern_sotho_pipeline_en.md
new file mode 100644
index 00000000000000..0c064aad4f5b16
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-rg_clean_signatures_southern_sotho_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English rg_clean_signatures_southern_sotho_pipeline pipeline DistilBertForTokenClassification from chilliadgl
+author: John Snow Labs
+name: rg_clean_signatures_southern_sotho_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rg_clean_signatures_southern_sotho_pipeline` is a English model originally trained by chilliadgl.
+
+{:.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/rg_clean_signatures_southern_sotho_pipeline_en_5.5.0_3.0_1725739674635.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rg_clean_signatures_southern_sotho_pipeline_en_5.5.0_3.0_1725739674635.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
+
+pipeline = PretrainedPipeline("rg_clean_signatures_southern_sotho_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rg_clean_signatures_southern_sotho_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rg_clean_signatures_southern_sotho_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/chilliadgl/RG_clean_signatures_ST
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-roberta_2020_q1_filtered_en.md b/docs/_posts/ahmedlone127/2024-09-07-roberta_2020_q1_filtered_en.md
new file mode 100644
index 00000000000000..f07ca73254c76a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-roberta_2020_q1_filtered_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_2020_q1_filtered RoBertaEmbeddings from DouglasPontes
+author: John Snow Labs
+name: roberta_2020_q1_filtered
+date: 2024-09-07
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_2020_q1_filtered` is a English model originally trained by DouglasPontes.
+
+{:.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/roberta_2020_q1_filtered_en_5.5.0_3.0_1725673258783.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_2020_q1_filtered_en_5.5.0_3.0_1725673258783.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_2020_q1_filtered","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_2020_q1_filtered","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_2020_q1_filtered|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|465.3 MB|
+
+## References
+
+https://huggingface.co/DouglasPontes/roberta-2020-Q1-filtered
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-roberta_base_indonesian_522m_id.md b/docs/_posts/ahmedlone127/2024-09-07-roberta_base_indonesian_522m_id.md
new file mode 100644
index 00000000000000..e9bbdc0ef4ceef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-roberta_base_indonesian_522m_id.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Indonesian roberta_base_indonesian_522m RoBertaEmbeddings from cahya
+author: John Snow Labs
+name: roberta_base_indonesian_522m
+date: 2024-09-07
+tags: [id, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: id
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_indonesian_522m` is a Indonesian model originally trained by cahya.
+
+{:.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/roberta_base_indonesian_522m_id_5.5.0_3.0_1725698300397.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_indonesian_522m_id_5.5.0_3.0_1725698300397.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_base_indonesian_522m","id") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_base_indonesian_522m","id") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_indonesian_522m|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|id|
+|Size:|470.7 MB|
+
+## References
+
+https://huggingface.co/cahya/roberta-base-indonesian-522M
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-roberta_base_indonesian_522m_pipeline_id.md b/docs/_posts/ahmedlone127/2024-09-07-roberta_base_indonesian_522m_pipeline_id.md
new file mode 100644
index 00000000000000..2a714450e946a5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-roberta_base_indonesian_522m_pipeline_id.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Indonesian roberta_base_indonesian_522m_pipeline pipeline RoBertaEmbeddings from cahya
+author: John Snow Labs
+name: roberta_base_indonesian_522m_pipeline
+date: 2024-09-07
+tags: [id, open_source, pipeline, onnx]
+task: Embeddings
+language: id
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_indonesian_522m_pipeline` is a Indonesian model originally trained by cahya.
+
+{:.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/roberta_base_indonesian_522m_pipeline_id_5.5.0_3.0_1725698321929.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_indonesian_522m_pipeline_id_5.5.0_3.0_1725698321929.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
+
+pipeline = PretrainedPipeline("roberta_base_indonesian_522m_pipeline", lang = "id")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_indonesian_522m_pipeline", lang = "id")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_indonesian_522m_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|id|
+|Size:|470.8 MB|
+
+## References
+
+https://huggingface.co/cahya/roberta-base-indonesian-522M
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-roberta_base_ner_demo_ganbold13_pipeline_mn.md b/docs/_posts/ahmedlone127/2024-09-07-roberta_base_ner_demo_ganbold13_pipeline_mn.md
new file mode 100644
index 00000000000000..ceb948e61559bf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-roberta_base_ner_demo_ganbold13_pipeline_mn.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Mongolian roberta_base_ner_demo_ganbold13_pipeline pipeline RoBertaForTokenClassification from ganbold13
+author: John Snow Labs
+name: roberta_base_ner_demo_ganbold13_pipeline
+date: 2024-09-07
+tags: [mn, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: mn
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_ner_demo_ganbold13_pipeline` is a Mongolian model originally trained by ganbold13.
+
+{:.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/roberta_base_ner_demo_ganbold13_pipeline_mn_5.5.0_3.0_1725720946427.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_ner_demo_ganbold13_pipeline_mn_5.5.0_3.0_1725720946427.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
+
+pipeline = PretrainedPipeline("roberta_base_ner_demo_ganbold13_pipeline", lang = "mn")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_ner_demo_ganbold13_pipeline", lang = "mn")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_ner_demo_ganbold13_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|mn|
+|Size:|465.7 MB|
+
+## References
+
+https://huggingface.co/ganbold13/roberta-base-ner-demo
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-roberta_classifier_large_realsumm_by_examples_fold2_en.md b/docs/_posts/ahmedlone127/2024-09-07-roberta_classifier_large_realsumm_by_examples_fold2_en.md
new file mode 100644
index 00000000000000..e03e2b860203e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-roberta_classifier_large_realsumm_by_examples_fold2_en.md
@@ -0,0 +1,104 @@
+---
+layout: model
+title: English RoBertaForSequenceClassification Large Cased model (from shiyue)
+author: John Snow Labs
+name: roberta_classifier_large_realsumm_by_examples_fold2
+date: 2024-09-07
+tags: [en, open_source, roberta, sequence_classification, classification, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-large-realsumm-by-examples-fold2` is a English model originally trained by `shiyue`.
+
+## Predicted Entities
+
+`entailment`, `contradiction`, `neutral`
+
+{:.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/roberta_classifier_large_realsumm_by_examples_fold2_en_5.5.0_3.0_1725717930713.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_classifier_large_realsumm_by_examples_fold2_en_5.5.0_3.0_1725717930713.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
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+seq_classifier = RoBertaForSequenceClassification.pretrained("roberta_classifier_large_realsumm_by_examples_fold2","en") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("class")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+      .setInputCols(Array("text"))
+      .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val seq_classifier = RoBertaForSequenceClassification.pretrained("roberta_classifier_large_realsumm_by_examples_fold2","en")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("class")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.classify.roberta.realsumm_by_examples_fold2.large.by_shiyue").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_classifier_large_realsumm_by_examples_fold2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+References
+
+- https://huggingface.co/shiyue/roberta-large-realsumm-by-examples-fold2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-roberta_large_finetuned_abbr_finetuned_ner_finetuned_ner_en.md b/docs/_posts/ahmedlone127/2024-09-07-roberta_large_finetuned_abbr_finetuned_ner_finetuned_ner_en.md
new file mode 100644
index 00000000000000..80b9788b749d62
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-roberta_large_finetuned_abbr_finetuned_ner_finetuned_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_large_finetuned_abbr_finetuned_ner_finetuned_ner RoBertaForTokenClassification from MinhMinh09
+author: John Snow Labs
+name: roberta_large_finetuned_abbr_finetuned_ner_finetuned_ner
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_finetuned_abbr_finetuned_ner_finetuned_ner` is a English model originally trained by MinhMinh09.
+
+{:.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/roberta_large_finetuned_abbr_finetuned_ner_finetuned_ner_en_5.5.0_3.0_1725723783037.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_finetuned_abbr_finetuned_ner_finetuned_ner_en_5.5.0_3.0_1725723783037.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_large_finetuned_abbr_finetuned_ner_finetuned_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_large_finetuned_abbr_finetuned_ner_finetuned_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_finetuned_abbr_finetuned_ner_finetuned_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/MinhMinh09/roberta-large-finetuned-abbr-finetuned-ner-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-roberta_large_pm_m3_voc_hf_finetuned_ner_anup7733_en.md b/docs/_posts/ahmedlone127/2024-09-07-roberta_large_pm_m3_voc_hf_finetuned_ner_anup7733_en.md
new file mode 100644
index 00000000000000..065a90e9b137eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-roberta_large_pm_m3_voc_hf_finetuned_ner_anup7733_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_large_pm_m3_voc_hf_finetuned_ner_anup7733 RoBertaForTokenClassification from Anup7733
+author: John Snow Labs
+name: roberta_large_pm_m3_voc_hf_finetuned_ner_anup7733
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_pm_m3_voc_hf_finetuned_ner_anup7733` is a English model originally trained by Anup7733.
+
+{:.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/roberta_large_pm_m3_voc_hf_finetuned_ner_anup7733_en_5.5.0_3.0_1725721731860.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_pm_m3_voc_hf_finetuned_ner_anup7733_en_5.5.0_3.0_1725721731860.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_large_pm_m3_voc_hf_finetuned_ner_anup7733","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_large_pm_m3_voc_hf_finetuned_ner_anup7733", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_pm_m3_voc_hf_finetuned_ner_anup7733|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Anup7733/RoBERTa-large-PM-M3-Voc-hf-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-roberta_large_pm_m3_voc_hf_finetuned_ner_anup7733_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-roberta_large_pm_m3_voc_hf_finetuned_ner_anup7733_pipeline_en.md
new file mode 100644
index 00000000000000..842e6ba1f2a3bf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-roberta_large_pm_m3_voc_hf_finetuned_ner_anup7733_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_large_pm_m3_voc_hf_finetuned_ner_anup7733_pipeline pipeline RoBertaForTokenClassification from Anup7733
+author: John Snow Labs
+name: roberta_large_pm_m3_voc_hf_finetuned_ner_anup7733_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_pm_m3_voc_hf_finetuned_ner_anup7733_pipeline` is a English model originally trained by Anup7733.
+
+{:.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/roberta_large_pm_m3_voc_hf_finetuned_ner_anup7733_pipeline_en_5.5.0_3.0_1725721801034.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_pm_m3_voc_hf_finetuned_ner_anup7733_pipeline_en_5.5.0_3.0_1725721801034.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
+
+pipeline = PretrainedPipeline("roberta_large_pm_m3_voc_hf_finetuned_ner_anup7733_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_large_pm_m3_voc_hf_finetuned_ner_anup7733_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_pm_m3_voc_hf_finetuned_ner_anup7733_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Anup7733/RoBERTa-large-PM-M3-Voc-hf-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-roberta_ner_rupesh2_en.md b/docs/_posts/ahmedlone127/2024-09-07-roberta_ner_rupesh2_en.md
new file mode 100644
index 00000000000000..80d330ce9ade75
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-roberta_ner_rupesh2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_ner_rupesh2 RoBertaForTokenClassification from Rupesh2
+author: John Snow Labs
+name: roberta_ner_rupesh2
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_ner_rupesh2` is a English model originally trained by Rupesh2.
+
+{:.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/roberta_ner_rupesh2_en_5.5.0_3.0_1725721562780.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_ner_rupesh2_en_5.5.0_3.0_1725721562780.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_ner_rupesh2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_ner_rupesh2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_ner_rupesh2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Rupesh2/roberta-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-roberta_psych_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-roberta_psych_pipeline_en.md
new file mode 100644
index 00000000000000..08ab0070fbbab4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-roberta_psych_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_psych_pipeline pipeline RoBertaEmbeddings from mlaricheva
+author: John Snow Labs
+name: roberta_psych_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_psych_pipeline` is a English model originally trained by mlaricheva.
+
+{:.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/roberta_psych_pipeline_en_5.5.0_3.0_1725677775220.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_psych_pipeline_en_5.5.0_3.0_1725677775220.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
+
+pipeline = PretrainedPipeline("roberta_psych_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_psych_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_psych_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|465.6 MB|
+
+## References
+
+https://huggingface.co/mlaricheva/roberta-psych
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-roberta_spanish_clinical_trials_misc_ents_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-roberta_spanish_clinical_trials_misc_ents_ner_pipeline_en.md
new file mode 100644
index 00000000000000..980d8293d134ff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-roberta_spanish_clinical_trials_misc_ents_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_spanish_clinical_trials_misc_ents_ner_pipeline pipeline RoBertaForTokenClassification from medspaner
+author: John Snow Labs
+name: roberta_spanish_clinical_trials_misc_ents_ner_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_spanish_clinical_trials_misc_ents_ner_pipeline` is a English model originally trained by medspaner.
+
+{:.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/roberta_spanish_clinical_trials_misc_ents_ner_pipeline_en_5.5.0_3.0_1725707814185.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_spanish_clinical_trials_misc_ents_ner_pipeline_en_5.5.0_3.0_1725707814185.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
+
+pipeline = PretrainedPipeline("roberta_spanish_clinical_trials_misc_ents_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_spanish_clinical_trials_misc_ents_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_spanish_clinical_trials_misc_ents_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|442.5 MB|
+
+## References
+
+https://huggingface.co/medspaner/roberta-es-clinical-trials-misc-ents-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-rubert_large_sberquad_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-rubert_large_sberquad_1_pipeline_en.md
new file mode 100644
index 00000000000000..e195b8aeed2f05
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-rubert_large_sberquad_1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English rubert_large_sberquad_1_pipeline pipeline BertForQuestionAnswering from Mathnub
+author: John Snow Labs
+name: rubert_large_sberquad_1_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_large_sberquad_1_pipeline` is a English model originally trained by Mathnub.
+
+{:.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/rubert_large_sberquad_1_pipeline_en_5.5.0_3.0_1725672220206.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_large_sberquad_1_pipeline_en_5.5.0_3.0_1725672220206.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
+
+pipeline = PretrainedPipeline("rubert_large_sberquad_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rubert_large_sberquad_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rubert_large_sberquad_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/Mathnub/rubert-large-sberquad-1
+
+## Included Models
+
+- MultiDocumentAssembler
+- BertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-run1_en.md b/docs/_posts/ahmedlone127/2024-09-07-run1_en.md
new file mode 100644
index 00000000000000..383c730a3eeaf4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-run1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English run1 MarianTransformer from mptrigo
+author: John Snow Labs
+name: run1
+date: 2024-09-07
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`run1` is a English model originally trained by mptrigo.
+
+{:.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/run1_en_5.5.0_3.0_1725741336687.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/run1_en_5.5.0_3.0_1725741336687.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("run1","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("run1","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|run1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|358.1 MB|
+
+## References
+
+https://huggingface.co/mptrigo/run1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-scoris_maltese_english_lithuanian_pipeline_lt.md b/docs/_posts/ahmedlone127/2024-09-07-scoris_maltese_english_lithuanian_pipeline_lt.md
new file mode 100644
index 00000000000000..acc32a6d693f41
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-scoris_maltese_english_lithuanian_pipeline_lt.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Lithuanian scoris_maltese_english_lithuanian_pipeline pipeline MarianTransformer from scoris
+author: John Snow Labs
+name: scoris_maltese_english_lithuanian_pipeline
+date: 2024-09-07
+tags: [lt, open_source, pipeline, onnx]
+task: Translation
+language: lt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scoris_maltese_english_lithuanian_pipeline` is a Lithuanian model originally trained by scoris.
+
+{:.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/scoris_maltese_english_lithuanian_pipeline_lt_5.5.0_3.0_1725740487142.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scoris_maltese_english_lithuanian_pipeline_lt_5.5.0_3.0_1725740487142.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
+
+pipeline = PretrainedPipeline("scoris_maltese_english_lithuanian_pipeline", lang = "lt")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("scoris_maltese_english_lithuanian_pipeline", lang = "lt")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|scoris_maltese_english_lithuanian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|lt|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/scoris/scoris-mt-en-lt
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-sent_afro_xlmr_base_finetuned_kintweetsc_en.md b/docs/_posts/ahmedlone127/2024-09-07-sent_afro_xlmr_base_finetuned_kintweetsc_en.md
new file mode 100644
index 00000000000000..563da5c673397b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-sent_afro_xlmr_base_finetuned_kintweetsc_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_afro_xlmr_base_finetuned_kintweetsc XlmRoBertaSentenceEmbeddings from RogerB
+author: John Snow Labs
+name: sent_afro_xlmr_base_finetuned_kintweetsc
+date: 2024-09-07
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+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.`sent_afro_xlmr_base_finetuned_kintweetsc` is a English model originally trained by RogerB.
+
+{:.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/sent_afro_xlmr_base_finetuned_kintweetsc_en_5.5.0_3.0_1725714675292.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_afro_xlmr_base_finetuned_kintweetsc_en_5.5.0_3.0_1725714675292.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_afro_xlmr_base_finetuned_kintweetsc","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_afro_xlmr_base_finetuned_kintweetsc","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_afro_xlmr_base_finetuned_kintweetsc|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/RogerB/afro-xlmr-base-finetuned-kintweetsC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-sent_agriculture_bert_uncased_en.md b/docs/_posts/ahmedlone127/2024-09-07-sent_agriculture_bert_uncased_en.md
new file mode 100644
index 00000000000000..a5a09c5a102c42
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-sent_agriculture_bert_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_agriculture_bert_uncased BertSentenceEmbeddings from recobo
+author: John Snow Labs
+name: sent_agriculture_bert_uncased
+date: 2024-09-07
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_agriculture_bert_uncased` is a English model originally trained by recobo.
+
+{:.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/sent_agriculture_bert_uncased_en_5.5.0_3.0_1725725429215.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_agriculture_bert_uncased_en_5.5.0_3.0_1725725429215.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_agriculture_bert_uncased","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_agriculture_bert_uncased","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_agriculture_bert_uncased|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.9 MB|
+
+## References
+
+https://huggingface.co/recobo/agriculture-bert-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-sent_agriculture_bert_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-sent_agriculture_bert_uncased_pipeline_en.md
new file mode 100644
index 00000000000000..b164c3cee5ff76
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-sent_agriculture_bert_uncased_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_agriculture_bert_uncased_pipeline pipeline BertSentenceEmbeddings from recobo
+author: John Snow Labs
+name: sent_agriculture_bert_uncased_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_agriculture_bert_uncased_pipeline` is a English model originally trained by recobo.
+
+{:.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/sent_agriculture_bert_uncased_pipeline_en_5.5.0_3.0_1725725447476.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_agriculture_bert_uncased_pipeline_en_5.5.0_3.0_1725725447476.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
+
+pipeline = PretrainedPipeline("sent_agriculture_bert_uncased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_agriculture_bert_uncased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_agriculture_bert_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|410.4 MB|
+
+## References
+
+https://huggingface.co/recobo/agriculture-bert-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-sent_bangla_bert_base_pipeline_bn.md b/docs/_posts/ahmedlone127/2024-09-07-sent_bangla_bert_base_pipeline_bn.md
new file mode 100644
index 00000000000000..2a4b31d5ca9dd8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-sent_bangla_bert_base_pipeline_bn.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Bengali sent_bangla_bert_base_pipeline pipeline BertSentenceEmbeddings from sagorsarker
+author: John Snow Labs
+name: sent_bangla_bert_base_pipeline
+date: 2024-09-07
+tags: [bn, open_source, pipeline, onnx]
+task: Embeddings
+language: bn
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bangla_bert_base_pipeline` is a Bengali model originally trained by sagorsarker.
+
+{:.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/sent_bangla_bert_base_pipeline_bn_5.5.0_3.0_1725724773105.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bangla_bert_base_pipeline_bn_5.5.0_3.0_1725724773105.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
+
+pipeline = PretrainedPipeline("sent_bangla_bert_base_pipeline", lang = "bn")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bangla_bert_base_pipeline", lang = "bn")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bangla_bert_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|bn|
+|Size:|615.3 MB|
+
+## References
+
+https://huggingface.co/sagorsarker/bangla-bert-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-sent_bert_1890_1900_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-sent_bert_1890_1900_pipeline_en.md
new file mode 100644
index 00000000000000..3986dcfadcf40f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-sent_bert_1890_1900_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_1890_1900_pipeline pipeline BertSentenceEmbeddings from Livingwithmachines
+author: John Snow Labs
+name: sent_bert_1890_1900_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_1890_1900_pipeline` is a English model originally trained by Livingwithmachines.
+
+{:.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/sent_bert_1890_1900_pipeline_en_5.5.0_3.0_1725701129070.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_1890_1900_pipeline_en_5.5.0_3.0_1725701129070.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
+
+pipeline = PretrainedPipeline("sent_bert_1890_1900_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_1890_1900_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_1890_1900_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.5 MB|
+
+## References
+
+https://huggingface.co/Livingwithmachines/bert_1890_1900
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-sent_bert_base_arabic_camelbert_msa_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-07-sent_bert_base_arabic_camelbert_msa_pipeline_ar.md
new file mode 100644
index 00000000000000..e12c3921bf7eb6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-sent_bert_base_arabic_camelbert_msa_pipeline_ar.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Arabic sent_bert_base_arabic_camelbert_msa_pipeline pipeline BertSentenceEmbeddings from CAMeL-Lab
+author: John Snow Labs
+name: sent_bert_base_arabic_camelbert_msa_pipeline
+date: 2024-09-07
+tags: [ar, open_source, pipeline, onnx]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_arabic_camelbert_msa_pipeline` is a Arabic model originally trained by CAMeL-Lab.
+
+{:.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/sent_bert_base_arabic_camelbert_msa_pipeline_ar_5.5.0_3.0_1725701009240.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_arabic_camelbert_msa_pipeline_ar_5.5.0_3.0_1725701009240.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
+
+pipeline = PretrainedPipeline("sent_bert_base_arabic_camelbert_msa_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_arabic_camelbert_msa_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_arabic_camelbert_msa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-msa
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-sent_bert_base_german_cased_oldvocab_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-07-sent_bert_base_german_cased_oldvocab_pipeline_de.md
new file mode 100644
index 00000000000000..76cabb06931449
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-sent_bert_base_german_cased_oldvocab_pipeline_de.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: German sent_bert_base_german_cased_oldvocab_pipeline pipeline BertSentenceEmbeddings from deepset
+author: John Snow Labs
+name: sent_bert_base_german_cased_oldvocab_pipeline
+date: 2024-09-07
+tags: [de, open_source, pipeline, onnx]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_german_cased_oldvocab_pipeline` is a German model originally trained by deepset.
+
+{:.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/sent_bert_base_german_cased_oldvocab_pipeline_de_5.5.0_3.0_1725725393263.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_german_cased_oldvocab_pipeline_de_5.5.0_3.0_1725725393263.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
+
+pipeline = PretrainedPipeline("sent_bert_base_german_cased_oldvocab_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_german_cased_oldvocab_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_german_cased_oldvocab_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|407.4 MB|
+
+## References
+
+https://huggingface.co/deepset/bert-base-german-cased-oldvocab
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-sent_bert_base_magicslabnu_en.md b/docs/_posts/ahmedlone127/2024-09-07-sent_bert_base_magicslabnu_en.md
new file mode 100644
index 00000000000000..8ee395de04f591
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-sent_bert_base_magicslabnu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_base_magicslabnu BertSentenceEmbeddings from magicslabnu
+author: John Snow Labs
+name: sent_bert_base_magicslabnu
+date: 2024-09-07
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_magicslabnu` is a English model originally trained by magicslabnu.
+
+{:.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/sent_bert_base_magicslabnu_en_5.5.0_3.0_1725700863758.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_magicslabnu_en_5.5.0_3.0_1725700863758.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_magicslabnu","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_magicslabnu","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_magicslabnu|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|408.4 MB|
+
+## References
+
+https://huggingface.co/magicslabnu/BERT_base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-sent_eq_bert_v1_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-sent_eq_bert_v1_1_pipeline_en.md
new file mode 100644
index 00000000000000..d44c7fcbc163fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-sent_eq_bert_v1_1_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_eq_bert_v1_1_pipeline pipeline BertSentenceEmbeddings from RyotaroOKabe
+author: John Snow Labs
+name: sent_eq_bert_v1_1_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_eq_bert_v1_1_pipeline` is a English model originally trained by RyotaroOKabe.
+
+{:.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/sent_eq_bert_v1_1_pipeline_en_5.5.0_3.0_1725748630637.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_eq_bert_v1_1_pipeline_en_5.5.0_3.0_1725748630637.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
+
+pipeline = PretrainedPipeline("sent_eq_bert_v1_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_eq_bert_v1_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_eq_bert_v1_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.8 MB|
+
+## References
+
+https://huggingface.co/RyotaroOKabe/eq_bert_v1.1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-sent_georgian_corpus_model_en.md b/docs/_posts/ahmedlone127/2024-09-07-sent_georgian_corpus_model_en.md
new file mode 100644
index 00000000000000..5dd008fd909644
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-sent_georgian_corpus_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_georgian_corpus_model BertSentenceEmbeddings from RichNachos
+author: John Snow Labs
+name: sent_georgian_corpus_model
+date: 2024-09-07
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_georgian_corpus_model` is a English model originally trained by RichNachos.
+
+{:.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/sent_georgian_corpus_model_en_5.5.0_3.0_1725724791537.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_georgian_corpus_model_en_5.5.0_3.0_1725724791537.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_georgian_corpus_model","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_georgian_corpus_model","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_georgian_corpus_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|107.1 MB|
+
+## References
+
+https://huggingface.co/RichNachos/georgian-corpus-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-sent_indo_aryan_xlm_r_base_gu.md b/docs/_posts/ahmedlone127/2024-09-07-sent_indo_aryan_xlm_r_base_gu.md
new file mode 100644
index 00000000000000..148e36639b5997
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-sent_indo_aryan_xlm_r_base_gu.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Gujarati sent_indo_aryan_xlm_r_base XlmRoBertaSentenceEmbeddings from ashwani-tanwar
+author: John Snow Labs
+name: sent_indo_aryan_xlm_r_base
+date: 2024-09-07
+tags: [gu, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: gu
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+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.`sent_indo_aryan_xlm_r_base` is a Gujarati model originally trained by ashwani-tanwar.
+
+{:.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/sent_indo_aryan_xlm_r_base_gu_5.5.0_3.0_1725738810984.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_indo_aryan_xlm_r_base_gu_5.5.0_3.0_1725738810984.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_indo_aryan_xlm_r_base","gu") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_indo_aryan_xlm_r_base","gu") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_indo_aryan_xlm_r_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|gu|
+|Size:|651.9 MB|
+
+## References
+
+https://huggingface.co/ashwani-tanwar/Indo-Aryan-XLM-R-Base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-sent_manubert_en.md b/docs/_posts/ahmedlone127/2024-09-07-sent_manubert_en.md
new file mode 100644
index 00000000000000..931d3c7cbe81f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-sent_manubert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_manubert BertSentenceEmbeddings from akumar33
+author: John Snow Labs
+name: sent_manubert
+date: 2024-09-07
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_manubert` is a English model originally trained by akumar33.
+
+{:.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/sent_manubert_en_5.5.0_3.0_1725749045676.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_manubert_en_5.5.0_3.0_1725749045676.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_manubert","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_manubert","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_manubert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/akumar33/ManuBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-sent_mika_safeaerobert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-sent_mika_safeaerobert_pipeline_en.md
new file mode 100644
index 00000000000000..317242f75af909
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-sent_mika_safeaerobert_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_mika_safeaerobert_pipeline pipeline BertSentenceEmbeddings from NASA-AIML
+author: John Snow Labs
+name: sent_mika_safeaerobert_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mika_safeaerobert_pipeline` is a English model originally trained by NASA-AIML.
+
+{:.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/sent_mika_safeaerobert_pipeline_en_5.5.0_3.0_1725737181777.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mika_safeaerobert_pipeline_en_5.5.0_3.0_1725737181777.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
+
+pipeline = PretrainedPipeline("sent_mika_safeaerobert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_mika_safeaerobert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mika_safeaerobert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/NASA-AIML/MIKA_SafeAeroBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-sent_patana_chilean_spanish_bert_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-07-sent_patana_chilean_spanish_bert_pipeline_es.md
new file mode 100644
index 00000000000000..358a66dc0091a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-sent_patana_chilean_spanish_bert_pipeline_es.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Castilian, Spanish sent_patana_chilean_spanish_bert_pipeline pipeline BertSentenceEmbeddings from dccuchile
+author: John Snow Labs
+name: sent_patana_chilean_spanish_bert_pipeline
+date: 2024-09-07
+tags: [es, open_source, pipeline, onnx]
+task: Embeddings
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_patana_chilean_spanish_bert_pipeline` is a Castilian, Spanish model originally trained by dccuchile.
+
+{:.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/sent_patana_chilean_spanish_bert_pipeline_es_5.5.0_3.0_1725749165294.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_patana_chilean_spanish_bert_pipeline_es_5.5.0_3.0_1725749165294.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
+
+pipeline = PretrainedPipeline("sent_patana_chilean_spanish_bert_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_patana_chilean_spanish_bert_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_patana_chilean_spanish_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|409.9 MB|
+
+## References
+
+https://huggingface.co/dccuchile/patana-chilean-spanish-bert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-sent_pretrained_xlm_portuguese_e8_select_en.md b/docs/_posts/ahmedlone127/2024-09-07-sent_pretrained_xlm_portuguese_e8_select_en.md
new file mode 100644
index 00000000000000..e26368ddaee190
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-sent_pretrained_xlm_portuguese_e8_select_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_pretrained_xlm_portuguese_e8_select XlmRoBertaSentenceEmbeddings from harish
+author: John Snow Labs
+name: sent_pretrained_xlm_portuguese_e8_select
+date: 2024-09-07
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+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.`sent_pretrained_xlm_portuguese_e8_select` is a English model originally trained by harish.
+
+{:.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/sent_pretrained_xlm_portuguese_e8_select_en_5.5.0_3.0_1725738324435.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_pretrained_xlm_portuguese_e8_select_en_5.5.0_3.0_1725738324435.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_pretrained_xlm_portuguese_e8_select","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_pretrained_xlm_portuguese_e8_select","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_pretrained_xlm_portuguese_e8_select|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/harish/preTrained-xlm-pt-e8-select
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-sent_rxbert_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-sent_rxbert_v1_pipeline_en.md
new file mode 100644
index 00000000000000..fd57341afc05d7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-sent_rxbert_v1_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_rxbert_v1_pipeline pipeline BertSentenceEmbeddings from seldas
+author: John Snow Labs
+name: sent_rxbert_v1_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_rxbert_v1_pipeline` is a English model originally trained by seldas.
+
+{:.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/sent_rxbert_v1_pipeline_en_5.5.0_3.0_1725725417062.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_rxbert_v1_pipeline_en_5.5.0_3.0_1725725417062.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
+
+pipeline = PretrainedPipeline("sent_rxbert_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_rxbert_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_rxbert_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.6 MB|
+
+## References
+
+https://huggingface.co/seldas/rxbert-v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-sent_turkish_tiny_bert_uncased_pipeline_tr.md b/docs/_posts/ahmedlone127/2024-09-07-sent_turkish_tiny_bert_uncased_pipeline_tr.md
new file mode 100644
index 00000000000000..02328ceec758e2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-sent_turkish_tiny_bert_uncased_pipeline_tr.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Turkish sent_turkish_tiny_bert_uncased_pipeline pipeline BertSentenceEmbeddings from ytu-ce-cosmos
+author: John Snow Labs
+name: sent_turkish_tiny_bert_uncased_pipeline
+date: 2024-09-07
+tags: [tr, open_source, pipeline, onnx]
+task: Embeddings
+language: tr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_turkish_tiny_bert_uncased_pipeline` is a Turkish model originally trained by ytu-ce-cosmos.
+
+{:.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/sent_turkish_tiny_bert_uncased_pipeline_tr_5.5.0_3.0_1725700835103.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_turkish_tiny_bert_uncased_pipeline_tr_5.5.0_3.0_1725700835103.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
+
+pipeline = PretrainedPipeline("sent_turkish_tiny_bert_uncased_pipeline", lang = "tr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_turkish_tiny_bert_uncased_pipeline", lang = "tr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_turkish_tiny_bert_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|tr|
+|Size:|17.9 MB|
+
+## References
+
+https://huggingface.co/ytu-ce-cosmos/turkish-tiny-bert-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-sent_vien_resume_roberta_base_en.md b/docs/_posts/ahmedlone127/2024-09-07-sent_vien_resume_roberta_base_en.md
new file mode 100644
index 00000000000000..fc591f132829cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-sent_vien_resume_roberta_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_vien_resume_roberta_base XlmRoBertaSentenceEmbeddings from thaidv96
+author: John Snow Labs
+name: sent_vien_resume_roberta_base
+date: 2024-09-07
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+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.`sent_vien_resume_roberta_base` is a English model originally trained by thaidv96.
+
+{:.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/sent_vien_resume_roberta_base_en_5.5.0_3.0_1725714257067.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_vien_resume_roberta_base_en_5.5.0_3.0_1725714257067.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_vien_resume_roberta_base","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_vien_resume_roberta_base","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_vien_resume_roberta_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/thaidv96/vien-resume-roberta-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-sent_xlm_roberta_base_finetuned_rugo_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-sent_xlm_roberta_base_finetuned_rugo_pipeline_en.md
new file mode 100644
index 00000000000000..671a97270bbfef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-sent_xlm_roberta_base_finetuned_rugo_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_rugo_pipeline pipeline XlmRoBertaSentenceEmbeddings from rugo
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_rugo_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_finetuned_rugo_pipeline` is a English model originally trained by rugo.
+
+{:.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/sent_xlm_roberta_base_finetuned_rugo_pipeline_en_5.5.0_3.0_1725683064081.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_rugo_pipeline_en_5.5.0_3.0_1725683064081.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
+
+pipeline = PretrainedPipeline("sent_xlm_roberta_base_finetuned_rugo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_xlm_roberta_base_finetuned_rugo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_rugo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|988.0 MB|
+
+## References
+
+https://huggingface.co/rugo/xlm-roberta-base-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-sent_xlm_roberta_base_finetuned_smcp_en.md b/docs/_posts/ahmedlone127/2024-09-07-sent_xlm_roberta_base_finetuned_smcp_en.md
new file mode 100644
index 00000000000000..03db45742c7450
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-sent_xlm_roberta_base_finetuned_smcp_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_smcp XlmRoBertaSentenceEmbeddings from sophiaaaa
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_smcp
+date: 2024-09-07
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+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.`sent_xlm_roberta_base_finetuned_smcp` is a English model originally trained by sophiaaaa.
+
+{:.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/sent_xlm_roberta_base_finetuned_smcp_en_5.5.0_3.0_1725682161219.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_smcp_en_5.5.0_3.0_1725682161219.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_smcp","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_smcp","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_smcp|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|944.2 MB|
+
+## References
+
+https://huggingface.co/sophiaaaa/xlm-roberta-base-finetuned-smcp
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-sent_zabantu_sot_ven_170m_ve.md b/docs/_posts/ahmedlone127/2024-09-07-sent_zabantu_sot_ven_170m_ve.md
new file mode 100644
index 00000000000000..2c9f7f7f47f68c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-sent_zabantu_sot_ven_170m_ve.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Venda sent_zabantu_sot_ven_170m XlmRoBertaSentenceEmbeddings from dsfsi
+author: John Snow Labs
+name: sent_zabantu_sot_ven_170m
+date: 2024-09-07
+tags: [ve, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: ve
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+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.`sent_zabantu_sot_ven_170m` is a Venda model originally trained by dsfsi.
+
+{:.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/sent_zabantu_sot_ven_170m_ve_5.5.0_3.0_1725714904467.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_zabantu_sot_ven_170m_ve_5.5.0_3.0_1725714904467.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_zabantu_sot_ven_170m","ve") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_zabantu_sot_ven_170m","ve") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_zabantu_sot_ven_170m|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|ve|
+|Size:|646.5 MB|
+
+## References
+
+https://huggingface.co/dsfsi/zabantu-sot-ven-170m
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-sentiment_analysis_azerbaijani_pipeline_az.md b/docs/_posts/ahmedlone127/2024-09-07-sentiment_analysis_azerbaijani_pipeline_az.md
new file mode 100644
index 00000000000000..990ce3a9de3beb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-sentiment_analysis_azerbaijani_pipeline_az.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Azerbaijani sentiment_analysis_azerbaijani_pipeline pipeline XlmRoBertaForSequenceClassification from LocalDoc
+author: John Snow Labs
+name: sentiment_analysis_azerbaijani_pipeline
+date: 2024-09-07
+tags: [az, open_source, pipeline, onnx]
+task: Text Classification
+language: az
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_analysis_azerbaijani_pipeline` is a Azerbaijani model originally trained by LocalDoc.
+
+{:.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/sentiment_analysis_azerbaijani_pipeline_az_5.5.0_3.0_1725711670642.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_analysis_azerbaijani_pipeline_az_5.5.0_3.0_1725711670642.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
+
+pipeline = PretrainedPipeline("sentiment_analysis_azerbaijani_pipeline", lang = "az")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sentiment_analysis_azerbaijani_pipeline", lang = "az")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_analysis_azerbaijani_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|az|
+|Size:|863.9 MB|
+
+## References
+
+https://huggingface.co/LocalDoc/sentiment_analysis_azerbaijani
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-setfit_model_misinformation_on_organizations_gofundme_wef_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-setfit_model_misinformation_on_organizations_gofundme_wef_pipeline_en.md
new file mode 100644
index 00000000000000..07a341990d8994
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-setfit_model_misinformation_on_organizations_gofundme_wef_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English setfit_model_misinformation_on_organizations_gofundme_wef_pipeline pipeline MPNetEmbeddings from mitra-mir
+author: John Snow Labs
+name: setfit_model_misinformation_on_organizations_gofundme_wef_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_model_misinformation_on_organizations_gofundme_wef_pipeline` is a English model originally trained by mitra-mir.
+
+{:.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/setfit_model_misinformation_on_organizations_gofundme_wef_pipeline_en_5.5.0_3.0_1725703316188.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_model_misinformation_on_organizations_gofundme_wef_pipeline_en_5.5.0_3.0_1725703316188.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
+
+pipeline = PretrainedPipeline("setfit_model_misinformation_on_organizations_gofundme_wef_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("setfit_model_misinformation_on_organizations_gofundme_wef_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|setfit_model_misinformation_on_organizations_gofundme_wef_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/mitra-mir/setfit-model-Misinformation-on-Organizations-GoFundMe-WEF
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-smm4h2024_task1_roberta_en.md b/docs/_posts/ahmedlone127/2024-09-07-smm4h2024_task1_roberta_en.md
new file mode 100644
index 00000000000000..cf468901148701
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-smm4h2024_task1_roberta_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English smm4h2024_task1_roberta RoBertaForTokenClassification from yseop
+author: John Snow Labs
+name: smm4h2024_task1_roberta
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`smm4h2024_task1_roberta` is a English model originally trained by yseop.
+
+{:.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/smm4h2024_task1_roberta_en_5.5.0_3.0_1725667766736.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/smm4h2024_task1_roberta_en_5.5.0_3.0_1725667766736.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("smm4h2024_task1_roberta","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("smm4h2024_task1_roberta", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|smm4h2024_task1_roberta|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|439.5 MB|
+
+## References
+
+https://huggingface.co/yseop/SMM4H2024_Task1_roberta
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-southern_sotho_all_mpnet_finetuned_french_1000_en.md b/docs/_posts/ahmedlone127/2024-09-07-southern_sotho_all_mpnet_finetuned_french_1000_en.md
new file mode 100644
index 00000000000000..6dcfc5c68006e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-southern_sotho_all_mpnet_finetuned_french_1000_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English southern_sotho_all_mpnet_finetuned_french_1000 MPNetEmbeddings from danfeg
+author: John Snow Labs
+name: southern_sotho_all_mpnet_finetuned_french_1000
+date: 2024-09-07
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`southern_sotho_all_mpnet_finetuned_french_1000` is a English model originally trained by danfeg.
+
+{:.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/southern_sotho_all_mpnet_finetuned_french_1000_en_5.5.0_3.0_1725703727644.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/southern_sotho_all_mpnet_finetuned_french_1000_en_5.5.0_3.0_1725703727644.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("southern_sotho_all_mpnet_finetuned_french_1000","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("southern_sotho_all_mpnet_finetuned_french_1000","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|southern_sotho_all_mpnet_finetuned_french_1000|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/danfeg/ST-ALL-MPNET_Finetuned-FR-1000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-spanish_capitalization_punctuation_restoration_sanivert_es.md b/docs/_posts/ahmedlone127/2024-09-07-spanish_capitalization_punctuation_restoration_sanivert_es.md
new file mode 100644
index 00000000000000..de4ec52ac299fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-spanish_capitalization_punctuation_restoration_sanivert_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish spanish_capitalization_punctuation_restoration_sanivert BertForTokenClassification from VOCALINLP
+author: John Snow Labs
+name: spanish_capitalization_punctuation_restoration_sanivert
+date: 2024-09-07
+tags: [es, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spanish_capitalization_punctuation_restoration_sanivert` is a Castilian, Spanish model originally trained by VOCALINLP.
+
+{:.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/spanish_capitalization_punctuation_restoration_sanivert_es_5.5.0_3.0_1725726612675.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spanish_capitalization_punctuation_restoration_sanivert_es_5.5.0_3.0_1725726612675.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("spanish_capitalization_punctuation_restoration_sanivert","es") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("spanish_capitalization_punctuation_restoration_sanivert", "es")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|spanish_capitalization_punctuation_restoration_sanivert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|es|
+|Size:|409.8 MB|
+
+## References
+
+https://huggingface.co/VOCALINLP/spanish_capitalization_punctuation_restoration_sanivert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-spea_3_en.md b/docs/_posts/ahmedlone127/2024-09-07-spea_3_en.md
new file mode 100644
index 00000000000000..3dbacc035fd60f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-spea_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English spea_3 RoBertaForSequenceClassification from BaronSch
+author: John Snow Labs
+name: spea_3
+date: 2024-09-07
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spea_3` is a English model originally trained by BaronSch.
+
+{:.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/spea_3_en_5.5.0_3.0_1725679759582.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spea_3_en_5.5.0_3.0_1725679759582.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("spea_3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("spea_3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|spea_3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|468.5 MB|
+
+## References
+
+https://huggingface.co/BaronSch/Spea_3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-stanford_deidentifier_only_radiology_reports_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-stanford_deidentifier_only_radiology_reports_pipeline_en.md
new file mode 100644
index 00000000000000..dcf7ccbbd4fc4c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-stanford_deidentifier_only_radiology_reports_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English stanford_deidentifier_only_radiology_reports_pipeline pipeline BertForTokenClassification from StanfordAIMI
+author: John Snow Labs
+name: stanford_deidentifier_only_radiology_reports_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`stanford_deidentifier_only_radiology_reports_pipeline` is a English model originally trained by StanfordAIMI.
+
+{:.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/stanford_deidentifier_only_radiology_reports_pipeline_en_5.5.0_3.0_1725726706741.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/stanford_deidentifier_only_radiology_reports_pipeline_en_5.5.0_3.0_1725726706741.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
+
+pipeline = PretrainedPipeline("stanford_deidentifier_only_radiology_reports_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("stanford_deidentifier_only_radiology_reports_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|stanford_deidentifier_only_radiology_reports_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.2 MB|
+
+## References
+
+https://huggingface.co/StanfordAIMI/stanford-deidentifier-only-radiology-reports
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-swiss_german_xlm_roberta_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-swiss_german_xlm_roberta_base_pipeline_en.md
new file mode 100644
index 00000000000000..472d097636bb20
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-swiss_german_xlm_roberta_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English swiss_german_xlm_roberta_base_pipeline pipeline XlmRoBertaEmbeddings from ZurichNLP
+author: John Snow Labs
+name: swiss_german_xlm_roberta_base_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swiss_german_xlm_roberta_base_pipeline` is a English model originally trained by ZurichNLP.
+
+{:.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/swiss_german_xlm_roberta_base_pipeline_en_5.5.0_3.0_1725676805040.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swiss_german_xlm_roberta_base_pipeline_en_5.5.0_3.0_1725676805040.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
+
+pipeline = PretrainedPipeline("swiss_german_xlm_roberta_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("swiss_german_xlm_roberta_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|swiss_german_xlm_roberta_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/ZurichNLP/swiss-german-xlm-roberta-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-terjman_large_v0_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-07-terjman_large_v0_pipeline_ar.md
new file mode 100644
index 00000000000000..be456e2c7015e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-terjman_large_v0_pipeline_ar.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Arabic terjman_large_v0_pipeline pipeline MarianTransformer from atlasia
+author: John Snow Labs
+name: terjman_large_v0_pipeline
+date: 2024-09-07
+tags: [ar, open_source, pipeline, onnx]
+task: Translation
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`terjman_large_v0_pipeline` is a Arabic model originally trained by atlasia.
+
+{:.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/terjman_large_v0_pipeline_ar_5.5.0_3.0_1725741872535.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/terjman_large_v0_pipeline_ar_5.5.0_3.0_1725741872535.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
+
+pipeline = PretrainedPipeline("terjman_large_v0_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("terjman_large_v0_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|terjman_large_v0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|1.4 GB|
+
+## References
+
+https://huggingface.co/atlasia/Terjman-Large-v0
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-test_demo_qa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-test_demo_qa_pipeline_en.md
new file mode 100644
index 00000000000000..6a19e15fdaae3c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-test_demo_qa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English test_demo_qa_pipeline pipeline DistilBertForQuestionAnswering from houyu0930
+author: John Snow Labs
+name: test_demo_qa_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_demo_qa_pipeline` is a English model originally trained by houyu0930.
+
+{:.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/test_demo_qa_pipeline_en_5.5.0_3.0_1725695743920.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_demo_qa_pipeline_en_5.5.0_3.0_1725695743920.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
+
+pipeline = PretrainedPipeline("test_demo_qa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test_demo_qa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_demo_qa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/houyu0930/test-demo-qa
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-testtesttest_en.md b/docs/_posts/ahmedlone127/2024-09-07-testtesttest_en.md
new file mode 100644
index 00000000000000..14a070067bdd5a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-testtesttest_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English testtesttest MarianTransformer from wrchen1
+author: John Snow Labs
+name: testtesttest
+date: 2024-09-07
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`testtesttest` is a English model originally trained by wrchen1.
+
+{:.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/testtesttest_en_5.5.0_3.0_1725747784352.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/testtesttest_en_5.5.0_3.0_1725747784352.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("testtesttest","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("testtesttest","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|testtesttest|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.4 MB|
+
+## References
+
+https://huggingface.co/wrchen1/testtesttest
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-toy_qa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-toy_qa_pipeline_en.md
new file mode 100644
index 00000000000000..5a79b8dbfcda8c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-toy_qa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English toy_qa_pipeline pipeline DistilBertForQuestionAnswering from datarpit
+author: John Snow Labs
+name: toy_qa_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`toy_qa_pipeline` is a English model originally trained by datarpit.
+
+{:.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/toy_qa_pipeline_en_5.5.0_3.0_1725695181765.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/toy_qa_pipeline_en_5.5.0_3.0_1725695181765.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
+
+pipeline = PretrainedPipeline("toy_qa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("toy_qa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|toy_qa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/datarpit/toy-qa
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-trail_kss_camembert_en.md b/docs/_posts/ahmedlone127/2024-09-07-trail_kss_camembert_en.md
new file mode 100644
index 00000000000000..df9ea7b515fb04
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-trail_kss_camembert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English trail_kss_camembert CamemBertEmbeddings from hltlab
+author: John Snow Labs
+name: trail_kss_camembert
+date: 2024-09-07
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trail_kss_camembert` is a English model originally trained by hltlab.
+
+{:.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/trail_kss_camembert_en_5.5.0_3.0_1725691657881.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trail_kss_camembert_en_5.5.0_3.0_1725691657881.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("trail_kss_camembert","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("trail_kss_camembert","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trail_kss_camembert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/hltlab/trail_kss-camembert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-trained_serbian_en.md b/docs/_posts/ahmedlone127/2024-09-07-trained_serbian_en.md
new file mode 100644
index 00000000000000..e4dc7a756e06df
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-trained_serbian_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English trained_serbian DistilBertForTokenClassification from annamariagnat
+author: John Snow Labs
+name: trained_serbian
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trained_serbian` is a English model originally trained by annamariagnat.
+
+{:.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/trained_serbian_en_5.5.0_3.0_1725729685083.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trained_serbian_en_5.5.0_3.0_1725729685083.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("trained_serbian","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("trained_serbian", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trained_serbian|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/annamariagnat/trained_serbian
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-trained_serbian_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-trained_serbian_pipeline_en.md
new file mode 100644
index 00000000000000..447a9f6044ba5d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-trained_serbian_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English trained_serbian_pipeline pipeline DistilBertForTokenClassification from annamariagnat
+author: John Snow Labs
+name: trained_serbian_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trained_serbian_pipeline` is a English model originally trained by annamariagnat.
+
+{:.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/trained_serbian_pipeline_en_5.5.0_3.0_1725729708363.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trained_serbian_pipeline_en_5.5.0_3.0_1725729708363.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
+
+pipeline = PretrainedPipeline("trained_serbian_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("trained_serbian_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trained_serbian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/annamariagnat/trained_serbian
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-translate_model_error_v0_1_en.md b/docs/_posts/ahmedlone127/2024-09-07-translate_model_error_v0_1_en.md
new file mode 100644
index 00000000000000..1985b307f4ae54
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-translate_model_error_v0_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English translate_model_error_v0_1 MarianTransformer from gshields
+author: John Snow Labs
+name: translate_model_error_v0_1
+date: 2024-09-07
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`translate_model_error_v0_1` is a English model originally trained by gshields.
+
+{:.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/translate_model_error_v0_1_en_5.5.0_3.0_1725747515067.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/translate_model_error_v0_1_en_5.5.0_3.0_1725747515067.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("translate_model_error_v0_1","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("translate_model_error_v0_1","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|translate_model_error_v0_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|523.0 MB|
+
+## References
+
+https://huggingface.co/gshields/translate_model_error_v0.1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-translate_model_error_v0_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-translate_model_error_v0_1_pipeline_en.md
new file mode 100644
index 00000000000000..bd01d6a1f2a6b6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-translate_model_error_v0_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English translate_model_error_v0_1_pipeline pipeline MarianTransformer from gshields
+author: John Snow Labs
+name: translate_model_error_v0_1_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`translate_model_error_v0_1_pipeline` is a English model originally trained by gshields.
+
+{:.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/translate_model_error_v0_1_pipeline_en_5.5.0_3.0_1725747539982.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/translate_model_error_v0_1_pipeline_en_5.5.0_3.0_1725747539982.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
+
+pipeline = PretrainedPipeline("translate_model_error_v0_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("translate_model_error_v0_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|translate_model_error_v0_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|523.5 MB|
+
+## References
+
+https://huggingface.co/gshields/translate_model_error_v0.1
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-translation_vietnamese_english_official_en.md b/docs/_posts/ahmedlone127/2024-09-07-translation_vietnamese_english_official_en.md
new file mode 100644
index 00000000000000..6628727a1e7ce7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-translation_vietnamese_english_official_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English translation_vietnamese_english_official MarianTransformer from NguyenManhAI
+author: John Snow Labs
+name: translation_vietnamese_english_official
+date: 2024-09-07
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`translation_vietnamese_english_official` is a English model originally trained by NguyenManhAI.
+
+{:.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/translation_vietnamese_english_official_en_5.5.0_3.0_1725741034785.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/translation_vietnamese_english_official_en_5.5.0_3.0_1725741034785.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("translation_vietnamese_english_official","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("translation_vietnamese_english_official","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|translation_vietnamese_english_official|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|474.6 MB|
+
+## References
+
+https://huggingface.co/NguyenManhAI/translation-vi-en-official
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-v2_mrcl0ud_en.md b/docs/_posts/ahmedlone127/2024-09-07-v2_mrcl0ud_en.md
new file mode 100644
index 00000000000000..c119f6e1feb1d2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-v2_mrcl0ud_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English v2_mrcl0ud DistilBertForQuestionAnswering from MrCl0ud
+author: John Snow Labs
+name: v2_mrcl0ud
+date: 2024-09-07
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`v2_mrcl0ud` is a English model originally trained by MrCl0ud.
+
+{:.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/v2_mrcl0ud_en_5.5.0_3.0_1725745598466.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/v2_mrcl0ud_en_5.5.0_3.0_1725745598466.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("v2_mrcl0ud","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("v2_mrcl0ud", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|v2_mrcl0ud|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/MrCl0ud/v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-vietnamese_distilbert_ner_en.md b/docs/_posts/ahmedlone127/2024-09-07-vietnamese_distilbert_ner_en.md
new file mode 100644
index 00000000000000..3aed75a7196191
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-vietnamese_distilbert_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vietnamese_distilbert_ner DistilBertForTokenClassification from quangtuyennguyen
+author: John Snow Labs
+name: vietnamese_distilbert_ner
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vietnamese_distilbert_ner` is a English model originally trained by quangtuyennguyen.
+
+{:.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/vietnamese_distilbert_ner_en_5.5.0_3.0_1725729946301.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vietnamese_distilbert_ner_en_5.5.0_3.0_1725729946301.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("vietnamese_distilbert_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("vietnamese_distilbert_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vietnamese_distilbert_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/quangtuyennguyen/Vi-DistilBert-NER
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-whisper_small_english_atco2_asr_en.md b/docs/_posts/ahmedlone127/2024-09-07-whisper_small_english_atco2_asr_en.md
new file mode 100644
index 00000000000000..a7e4fdfc605f2d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-whisper_small_english_atco2_asr_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English whisper_small_english_atco2_asr WhisperForCTC from jlvdoorn
+author: John Snow Labs
+name: whisper_small_english_atco2_asr
+date: 2024-09-07
+tags: [en, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_english_atco2_asr` is a English model originally trained by jlvdoorn.
+
+{:.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/whisper_small_english_atco2_asr_en_5.5.0_3.0_1725750282737.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_english_atco2_asr_en_5.5.0_3.0_1725750282737.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
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_small_english_atco2_asr","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_small_english_atco2_asr", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_english_atco2_asr|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/jlvdoorn/whisper-small.en-atco2-asr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-whisper_small_finetunedenglish_speechfinal_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-whisper_small_finetunedenglish_speechfinal_pipeline_en.md
new file mode 100644
index 00000000000000..41446259027b03
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-whisper_small_finetunedenglish_speechfinal_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English whisper_small_finetunedenglish_speechfinal_pipeline pipeline WhisperForCTC from tonybegemy
+author: John Snow Labs
+name: whisper_small_finetunedenglish_speechfinal_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_finetunedenglish_speechfinal_pipeline` is a English model originally trained by tonybegemy.
+
+{:.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/whisper_small_finetunedenglish_speechfinal_pipeline_en_5.5.0_3.0_1725749951451.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_finetunedenglish_speechfinal_pipeline_en_5.5.0_3.0_1725749951451.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
+
+pipeline = PretrainedPipeline("whisper_small_finetunedenglish_speechfinal_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_small_finetunedenglish_speechfinal_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_finetunedenglish_speechfinal_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/tonybegemy/whisper_small_finetunedenglish_speechfinal
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-whisper_small_russian_v2_artyomboyko_pipeline_ru.md b/docs/_posts/ahmedlone127/2024-09-07-whisper_small_russian_v2_artyomboyko_pipeline_ru.md
new file mode 100644
index 00000000000000..1fb37a4e169e38
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-whisper_small_russian_v2_artyomboyko_pipeline_ru.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Russian whisper_small_russian_v2_artyomboyko_pipeline pipeline WhisperForCTC from artyomboyko
+author: John Snow Labs
+name: whisper_small_russian_v2_artyomboyko_pipeline
+date: 2024-09-07
+tags: [ru, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: ru
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_russian_v2_artyomboyko_pipeline` is a Russian model originally trained by artyomboyko.
+
+{:.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/whisper_small_russian_v2_artyomboyko_pipeline_ru_5.5.0_3.0_1725752047300.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_russian_v2_artyomboyko_pipeline_ru_5.5.0_3.0_1725752047300.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
+
+pipeline = PretrainedPipeline("whisper_small_russian_v2_artyomboyko_pipeline", lang = "ru")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_small_russian_v2_artyomboyko_pipeline", lang = "ru")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_russian_v2_artyomboyko_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ru|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/artyomboyko/whisper-small-ru-v2
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-whisper_tiny_ft_welsh_english_cy.md b/docs/_posts/ahmedlone127/2024-09-07-whisper_tiny_ft_welsh_english_cy.md
new file mode 100644
index 00000000000000..1ac268c76c8c7f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-whisper_tiny_ft_welsh_english_cy.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Welsh whisper_tiny_ft_welsh_english WhisperForCTC from techiaith
+author: John Snow Labs
+name: whisper_tiny_ft_welsh_english
+date: 2024-09-07
+tags: [cy, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: cy
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_tiny_ft_welsh_english` is a Welsh model originally trained by techiaith.
+
+{:.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/whisper_tiny_ft_welsh_english_cy_5.5.0_3.0_1725752081418.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_ft_welsh_english_cy_5.5.0_3.0_1725752081418.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
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_tiny_ft_welsh_english","cy") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_tiny_ft_welsh_english", "cy")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_tiny_ft_welsh_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|cy|
+|Size:|389.6 MB|
+
+## References
+
+https://huggingface.co/techiaith/whisper-tiny-ft-cy-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-whisper_tiny_ft_welsh_english_pipeline_cy.md b/docs/_posts/ahmedlone127/2024-09-07-whisper_tiny_ft_welsh_english_pipeline_cy.md
new file mode 100644
index 00000000000000..0dc95e5e52cddc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-whisper_tiny_ft_welsh_english_pipeline_cy.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Welsh whisper_tiny_ft_welsh_english_pipeline pipeline WhisperForCTC from techiaith
+author: John Snow Labs
+name: whisper_tiny_ft_welsh_english_pipeline
+date: 2024-09-07
+tags: [cy, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: cy
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_tiny_ft_welsh_english_pipeline` is a Welsh model originally trained by techiaith.
+
+{:.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/whisper_tiny_ft_welsh_english_pipeline_cy_5.5.0_3.0_1725752104784.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_ft_welsh_english_pipeline_cy_5.5.0_3.0_1725752104784.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
+
+pipeline = PretrainedPipeline("whisper_tiny_ft_welsh_english_pipeline", lang = "cy")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_tiny_ft_welsh_english_pipeline", lang = "cy")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_tiny_ft_welsh_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|cy|
+|Size:|389.6 MB|
+
+## References
+
+https://huggingface.co/techiaith/whisper-tiny-ft-cy-en
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-whisper_tiny_portuguese_dominguesm_pipeline_pt.md b/docs/_posts/ahmedlone127/2024-09-07-whisper_tiny_portuguese_dominguesm_pipeline_pt.md
new file mode 100644
index 00000000000000..a044683aeccbb6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-whisper_tiny_portuguese_dominguesm_pipeline_pt.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Portuguese whisper_tiny_portuguese_dominguesm_pipeline pipeline WhisperForCTC from dominguesm
+author: John Snow Labs
+name: whisper_tiny_portuguese_dominguesm_pipeline
+date: 2024-09-07
+tags: [pt, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: pt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_tiny_portuguese_dominguesm_pipeline` is a Portuguese model originally trained by dominguesm.
+
+{:.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/whisper_tiny_portuguese_dominguesm_pipeline_pt_5.5.0_3.0_1725752490010.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_portuguese_dominguesm_pipeline_pt_5.5.0_3.0_1725752490010.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
+
+pipeline = PretrainedPipeline("whisper_tiny_portuguese_dominguesm_pipeline", lang = "pt")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_tiny_portuguese_dominguesm_pipeline", lang = "pt")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_tiny_portuguese_dominguesm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|pt|
+|Size:|390.8 MB|
+
+## References
+
+https://huggingface.co/dominguesm/whisper-tiny-pt
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-wolof_finetuned_ner_en.md b/docs/_posts/ahmedlone127/2024-09-07-wolof_finetuned_ner_en.md
new file mode 100644
index 00000000000000..2b134ce43a092e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-wolof_finetuned_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English wolof_finetuned_ner XlmRoBertaForTokenClassification from vonewman
+author: John Snow Labs
+name: wolof_finetuned_ner
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wolof_finetuned_ner` is a English model originally trained by vonewman.
+
+{:.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/wolof_finetuned_ner_en_5.5.0_3.0_1725745134997.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wolof_finetuned_ner_en_5.5.0_3.0_1725745134997.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("wolof_finetuned_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("wolof_finetuned_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|wolof_finetuned_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|777.5 MB|
+
+## References
+
+https://huggingface.co/vonewman/wolof-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_final_vietnam_aug_insert_w2v_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_final_vietnam_aug_insert_w2v_2_pipeline_en.md
new file mode 100644
index 00000000000000..da76438c073c1f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_final_vietnam_aug_insert_w2v_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_final_vietnam_aug_insert_w2v_2_pipeline pipeline XlmRoBertaForSequenceClassification from ThuyNT03
+author: John Snow Labs
+name: xlm_roberta_base_final_vietnam_aug_insert_w2v_2_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_final_vietnam_aug_insert_w2v_2_pipeline` is a English model originally trained by ThuyNT03.
+
+{:.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/xlm_roberta_base_final_vietnam_aug_insert_w2v_2_pipeline_en_5.5.0_3.0_1725669535598.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_vietnam_aug_insert_w2v_2_pipeline_en_5.5.0_3.0_1725669535598.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_final_vietnam_aug_insert_w2v_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_final_vietnam_aug_insert_w2v_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_final_vietnam_aug_insert_w2v_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|795.9 MB|
+
+## References
+
+https://huggingface.co/ThuyNT03/xlm-roberta-base-Final_VietNam-aug_insert_w2v-2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_2_en.md b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_2_en.md
new file mode 100644
index 00000000000000..c844751a3ec041
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_2 XlmRoBertaForQuestionAnswering from jluckyboyj
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_2
+date: 2024-09-07
+tags: [en, open_source, onnx, question_answering, xlm_roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_2` is a English model originally trained by jluckyboyj.
+
+{:.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/xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_2_en_5.5.0_3.0_1725686218563.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_2_en_5.5.0_3.0_1725686218563.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_2","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = XlmRoBertaForQuestionAnswering.pretrained("xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_augument_visquad2_14_3_2023_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|853.2 MB|
+
+## References
+
+https://huggingface.co/jluckyboyj/xlm-roberta-base-finetuned-augument-visquad2-14-3-2023-2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_marc_yuri_en.md b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_marc_yuri_en.md
new file mode 100644
index 00000000000000..356a5c41290e8f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_marc_yuri_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_marc_yuri XlmRoBertaForSequenceClassification from Yuri
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_marc_yuri
+date: 2024-09-07
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_marc_yuri` is a English model originally trained by Yuri.
+
+{:.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/xlm_roberta_base_finetuned_marc_yuri_en_5.5.0_3.0_1725712867173.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_marc_yuri_en_5.5.0_3.0_1725712867173.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_marc_yuri","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_finetuned_marc_yuri", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_marc_yuri|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|835.1 MB|
+
+## References
+
+https://huggingface.co/Yuri/xlm-roberta-base-finetuned-marc
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_all_ahmad_alismail_en.md b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_all_ahmad_alismail_en.md
new file mode 100644
index 00000000000000..f6553dd411fbec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_all_ahmad_alismail_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_ahmad_alismail XlmRoBertaForTokenClassification from ahmad-alismail
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_ahmad_alismail
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_ahmad_alismail` is a English model originally trained by ahmad-alismail.
+
+{:.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/xlm_roberta_base_finetuned_panx_all_ahmad_alismail_en_5.5.0_3.0_1725687163542.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_ahmad_alismail_en_5.5.0_3.0_1725687163542.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_ahmad_alismail","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_ahmad_alismail", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_ahmad_alismail|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|858.2 MB|
+
+## References
+
+https://huggingface.co/ahmad-alismail/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_all_cataluna84_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_all_cataluna84_pipeline_en.md
new file mode 100644
index 00000000000000..aee7cfd5d2db50
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_all_cataluna84_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_cataluna84_pipeline pipeline XlmRoBertaForTokenClassification from cataluna84
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_cataluna84_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_cataluna84_pipeline` is a English model originally trained by cataluna84.
+
+{:.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/xlm_roberta_base_finetuned_panx_all_cataluna84_pipeline_en_5.5.0_3.0_1725688124726.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_cataluna84_pipeline_en_5.5.0_3.0_1725688124726.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_cataluna84_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_cataluna84_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_cataluna84_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|861.0 MB|
+
+## References
+
+https://huggingface.co/cataluna84/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_english_bessho_en.md b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_english_bessho_en.md
new file mode 100644
index 00000000000000..6454e174240bf8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_english_bessho_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_bessho XlmRoBertaForTokenClassification from bessho
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_bessho
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_bessho` is a English model originally trained by bessho.
+
+{:.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/xlm_roberta_base_finetuned_panx_english_bessho_en_5.5.0_3.0_1725743402059.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_bessho_en_5.5.0_3.0_1725743402059.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_bessho","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_bessho", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_bessho|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|826.4 MB|
+
+## References
+
+https://huggingface.co/bessho/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_english_drigb_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_english_drigb_pipeline_en.md
new file mode 100644
index 00000000000000..075ede3e0ee0f4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_english_drigb_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_drigb_pipeline pipeline XlmRoBertaForTokenClassification from drigb
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_drigb_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_drigb_pipeline` is a English model originally trained by drigb.
+
+{:.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/xlm_roberta_base_finetuned_panx_english_drigb_pipeline_en_5.5.0_3.0_1725704615630.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_drigb_pipeline_en_5.5.0_3.0_1725704615630.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_drigb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_drigb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_drigb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|826.4 MB|
+
+## References
+
+https://huggingface.co/drigb/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_french_ferro_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_french_ferro_pipeline_en.md
new file mode 100644
index 00000000000000..58dc9038113745
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_french_ferro_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_ferro_pipeline pipeline XlmRoBertaForTokenClassification from Ferro
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_ferro_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_ferro_pipeline` is a English model originally trained by Ferro.
+
+{:.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/xlm_roberta_base_finetuned_panx_french_ferro_pipeline_en_5.5.0_3.0_1725744433465.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_ferro_pipeline_en_5.5.0_3.0_1725744433465.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_ferro_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_ferro_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_ferro_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.9 MB|
+
+## References
+
+https://huggingface.co/Ferro/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_french_robkayinto_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_french_robkayinto_pipeline_en.md
new file mode 100644
index 00000000000000..e870efb30b9a52
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_french_robkayinto_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_robkayinto_pipeline pipeline XlmRoBertaForTokenClassification from robkayinto
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_robkayinto_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_robkayinto_pipeline` is a English model originally trained by robkayinto.
+
+{:.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/xlm_roberta_base_finetuned_panx_french_robkayinto_pipeline_en_5.5.0_3.0_1725694407897.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_robkayinto_pipeline_en_5.5.0_3.0_1725694407897.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_robkayinto_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_robkayinto_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_robkayinto_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.9 MB|
+
+## References
+
+https://huggingface.co/robkayinto/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_german_cicimen_en.md b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_german_cicimen_en.md
new file mode 100644
index 00000000000000..fb051453461946
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_german_cicimen_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_cicimen XlmRoBertaForTokenClassification from cicimen
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_cicimen
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_cicimen` is a English model originally trained by cicimen.
+
+{:.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/xlm_roberta_base_finetuned_panx_german_cicimen_en_5.5.0_3.0_1725687770570.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_cicimen_en_5.5.0_3.0_1725687770570.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_cicimen","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_cicimen", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_cicimen|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/cicimen/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_german_french_laurentiustancioiu_en.md b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_german_french_laurentiustancioiu_en.md
new file mode 100644
index 00000000000000..38ee9e06f828e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_german_french_laurentiustancioiu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_laurentiustancioiu XlmRoBertaForTokenClassification from LaurentiuStancioiu
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_laurentiustancioiu
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_laurentiustancioiu` is a English model originally trained by LaurentiuStancioiu.
+
+{:.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/xlm_roberta_base_finetuned_panx_german_french_laurentiustancioiu_en_5.5.0_3.0_1725705080243.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_laurentiustancioiu_en_5.5.0_3.0_1725705080243.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_laurentiustancioiu","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_laurentiustancioiu", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_laurentiustancioiu|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|858.2 MB|
+
+## References
+
+https://huggingface.co/LaurentiuStancioiu/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_german_gus07ven_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_german_gus07ven_pipeline_en.md
new file mode 100644
index 00000000000000..a1b9cd8662dc71
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_german_gus07ven_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_gus07ven_pipeline pipeline XlmRoBertaForTokenClassification from gus07ven
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_gus07ven_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_gus07ven_pipeline` is a English model originally trained by gus07ven.
+
+{:.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/xlm_roberta_base_finetuned_panx_german_gus07ven_pipeline_en_5.5.0_3.0_1725743628094.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_gus07ven_pipeline_en_5.5.0_3.0_1725743628094.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_gus07ven_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_gus07ven_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_gus07ven_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/gus07ven/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_german_huangjia_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_german_huangjia_pipeline_en.md
new file mode 100644
index 00000000000000..6b4a2ec1e122c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_german_huangjia_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_huangjia_pipeline pipeline XlmRoBertaForTokenClassification from huangjia
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_huangjia_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_huangjia_pipeline` is a English model originally trained by huangjia.
+
+{:.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/xlm_roberta_base_finetuned_panx_german_huangjia_pipeline_en_5.5.0_3.0_1725745296258.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_huangjia_pipeline_en_5.5.0_3.0_1725745296258.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_huangjia_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_huangjia_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_huangjia_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|851.8 MB|
+
+## References
+
+https://huggingface.co/huangjia/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_german_jfmatos_isq_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_german_jfmatos_isq_pipeline_en.md
new file mode 100644
index 00000000000000..1e5b30293d7fa5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_german_jfmatos_isq_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_jfmatos_isq_pipeline pipeline XlmRoBertaForTokenClassification from jfmatos-isq
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_jfmatos_isq_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_jfmatos_isq_pipeline` is a English model originally trained by jfmatos-isq.
+
+{:.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/xlm_roberta_base_finetuned_panx_german_jfmatos_isq_pipeline_en_5.5.0_3.0_1725688909827.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_jfmatos_isq_pipeline_en_5.5.0_3.0_1725688909827.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_jfmatos_isq_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_jfmatos_isq_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_jfmatos_isq_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/jfmatos-isq/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_german_k4west_en.md b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_german_k4west_en.md
new file mode 100644
index 00000000000000..cc4faf4ab706e3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_german_k4west_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_k4west XlmRoBertaForTokenClassification from k4west
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_k4west
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_k4west` is a English model originally trained by k4west.
+
+{:.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/xlm_roberta_base_finetuned_panx_german_k4west_en_5.5.0_3.0_1725704910237.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_k4west_en_5.5.0_3.0_1725704910237.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_k4west","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_k4west", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_k4west|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/k4west/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_german_xiao888_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_german_xiao888_pipeline_en.md
new file mode 100644
index 00000000000000..54bd25d81291ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_german_xiao888_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_xiao888_pipeline pipeline XlmRoBertaForTokenClassification from Xiao888
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_xiao888_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_xiao888_pipeline` is a English model originally trained by Xiao888.
+
+{:.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/xlm_roberta_base_finetuned_panx_german_xiao888_pipeline_en_5.5.0_3.0_1725688491445.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_xiao888_pipeline_en_5.5.0_3.0_1725688491445.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_xiao888_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_xiao888_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_xiao888_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/Xiao888/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_german_yoyoyo1118_en.md b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_german_yoyoyo1118_en.md
new file mode 100644
index 00000000000000..b3491ba956cbc1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_german_yoyoyo1118_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_yoyoyo1118 XlmRoBertaForTokenClassification from yoyoyo1118
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_yoyoyo1118
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_yoyoyo1118` is a English model originally trained by yoyoyo1118.
+
+{:.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/xlm_roberta_base_finetuned_panx_german_yoyoyo1118_en_5.5.0_3.0_1725744584622.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_yoyoyo1118_en_5.5.0_3.0_1725744584622.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_yoyoyo1118","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_yoyoyo1118", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_yoyoyo1118|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/yoyoyo1118/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_german_yoyoyo1118_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_german_yoyoyo1118_pipeline_en.md
new file mode 100644
index 00000000000000..c71e01db0684e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_german_yoyoyo1118_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_yoyoyo1118_pipeline pipeline XlmRoBertaForTokenClassification from yoyoyo1118
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_yoyoyo1118_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_yoyoyo1118_pipeline` is a English model originally trained by yoyoyo1118.
+
+{:.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/xlm_roberta_base_finetuned_panx_german_yoyoyo1118_pipeline_en_5.5.0_3.0_1725744650355.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_yoyoyo1118_pipeline_en_5.5.0_3.0_1725744650355.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_yoyoyo1118_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_yoyoyo1118_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_yoyoyo1118_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/yoyoyo1118/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_italian_munsu_en.md b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_italian_munsu_en.md
new file mode 100644
index 00000000000000..482b2e39c3c8f2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_finetuned_panx_italian_munsu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_munsu XlmRoBertaForTokenClassification from MunSu
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_munsu
+date: 2024-09-07
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_munsu` is a English model originally trained by MunSu.
+
+{:.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/xlm_roberta_base_finetuned_panx_italian_munsu_en_5.5.0_3.0_1725693864058.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_munsu_en_5.5.0_3.0_1725693864058.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_munsu","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_munsu", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_munsu|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|860.1 MB|
+
+## References
+
+https://huggingface.co/MunSu/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_ukrainian_ner_ukrner_pipeline_uk.md b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_ukrainian_ner_ukrner_pipeline_uk.md
new file mode 100644
index 00000000000000..55f0c225b0f28d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-xlm_roberta_base_ukrainian_ner_ukrner_pipeline_uk.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Ukrainian xlm_roberta_base_ukrainian_ner_ukrner_pipeline pipeline XlmRoBertaForTokenClassification from EvanD
+author: John Snow Labs
+name: xlm_roberta_base_ukrainian_ner_ukrner_pipeline
+date: 2024-09-07
+tags: [uk, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: uk
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_ukrainian_ner_ukrner_pipeline` is a Ukrainian model originally trained by EvanD.
+
+{:.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/xlm_roberta_base_ukrainian_ner_ukrner_pipeline_uk_5.5.0_3.0_1725743325332.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_ukrainian_ner_ukrner_pipeline_uk_5.5.0_3.0_1725743325332.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_ukrainian_ner_ukrner_pipeline", lang = "uk")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_ukrainian_ner_ukrner_pipeline", lang = "uk")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_ukrainian_ner_ukrner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|uk|
+|Size:|785.4 MB|
+
+## References
+
+https://huggingface.co/EvanD/xlm-roberta-base-ukrainian-ner-ukrner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-xlmr_base_toxicity_classifier_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-07-xlmr_base_toxicity_classifier_pipeline_xx.md
new file mode 100644
index 00000000000000..600d330e7f10cd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-xlmr_base_toxicity_classifier_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual xlmr_base_toxicity_classifier_pipeline pipeline XlmRoBertaForSequenceClassification from textdetox
+author: John Snow Labs
+name: xlmr_base_toxicity_classifier_pipeline
+date: 2024-09-07
+tags: [xx, open_source, pipeline, onnx]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_base_toxicity_classifier_pipeline` is a Multilingual model originally trained by textdetox.
+
+{:.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/xlmr_base_toxicity_classifier_pipeline_xx_5.5.0_3.0_1725670944247.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_base_toxicity_classifier_pipeline_xx_5.5.0_3.0_1725670944247.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
+
+pipeline = PretrainedPipeline("xlmr_base_toxicity_classifier_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmr_base_toxicity_classifier_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_base_toxicity_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|876.6 MB|
+
+## References
+
+https://huggingface.co/textdetox/xlmr-base-toxicity-classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-xlmr_finetuned_qasrl_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-xlmr_finetuned_qasrl_pipeline_en.md
new file mode 100644
index 00000000000000..c30dc4be1da879
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-xlmr_finetuned_qasrl_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English xlmr_finetuned_qasrl_pipeline pipeline XlmRoBertaForQuestionAnswering from lielbin
+author: John Snow Labs
+name: xlmr_finetuned_qasrl_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_finetuned_qasrl_pipeline` is a English model originally trained by lielbin.
+
+{:.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/xlmr_finetuned_qasrl_pipeline_en_5.5.0_3.0_1725685649459.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_finetuned_qasrl_pipeline_en_5.5.0_3.0_1725685649459.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
+
+pipeline = PretrainedPipeline("xlmr_finetuned_qasrl_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmr_finetuned_qasrl_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_finetuned_qasrl_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|859.3 MB|
+
+## References
+
+https://huggingface.co/lielbin/XLMR-finetuned-QASRL
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-xlmr_webis_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-xlmr_webis_pipeline_en.md
new file mode 100644
index 00000000000000..f59df480f8c6f4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-xlmr_webis_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English xlmr_webis_pipeline pipeline XlmRoBertaForQuestionAnswering from intanm
+author: John Snow Labs
+name: xlmr_webis_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_webis_pipeline` is a English model originally trained by intanm.
+
+{:.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/xlmr_webis_pipeline_en_5.5.0_3.0_1725686482823.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_webis_pipeline_en_5.5.0_3.0_1725686482823.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
+
+pipeline = PretrainedPipeline("xlmr_webis_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmr_webis_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_webis_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|826.4 MB|
+
+## References
+
+https://huggingface.co/intanm/xlmr-webis
+
+## Included Models
+
+- MultiDocumentAssembler
+- XlmRoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-xlmroberta_ner_aytugkaya_base_finetuned_panx_de.md b/docs/_posts/ahmedlone127/2024-09-07-xlmroberta_ner_aytugkaya_base_finetuned_panx_de.md
new file mode 100644
index 00000000000000..b555f3ded7bc91
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-xlmroberta_ner_aytugkaya_base_finetuned_panx_de.md
@@ -0,0 +1,113 @@
+---
+layout: model
+title: German XLMRobertaForTokenClassification Base Cased model (from aytugkaya)
+author: John Snow Labs
+name: xlmroberta_ner_aytugkaya_base_finetuned_panx
+date: 2024-09-07
+tags: [de, open_source, xlm_roberta, ner, onnx]
+task: Named Entity Recognition
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-panx-de` is a German model originally trained by `aytugkaya`.
+
+## Predicted Entities
+
+`PER`, `LOC`, `ORG`
+
+{:.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/xlmroberta_ner_aytugkaya_base_finetuned_panx_de_5.5.0_3.0_1725743913469.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_aytugkaya_base_finetuned_panx_de_5.5.0_3.0_1725743913469.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
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_aytugkaya_base_finetuned_panx","de") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+ner_converter = NerConverter()\
+    .setInputCols(["document", "token", "ner"])\
+    .setOutputCol("ner_chunk")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+      .setInputCols(Array("text"))
+      .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_aytugkaya_base_finetuned_panx","de")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val ner_converter = new NerConverter()
+    .setInputCols(Array("document", "token', "ner"))
+    .setOutputCol("ner_chunk")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("de.ner.xlmr_roberta.xtreme.base_finetuned.by_aytugkaya").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_aytugkaya_base_finetuned_panx|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|de|
+|Size:|853.7 MB|
+
+## References
+
+References
+
+- https://huggingface.co/aytugkaya/xlm-roberta-base-finetuned-panx-de
+- https://paperswithcode.com/sota?task=Token+Classification&dataset=xtreme
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-xlmroberta_ner_base_fin_fi.md b/docs/_posts/ahmedlone127/2024-09-07-xlmroberta_ner_base_fin_fi.md
new file mode 100644
index 00000000000000..cf9b97756c0ea6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-xlmroberta_ner_base_fin_fi.md
@@ -0,0 +1,113 @@
+---
+layout: model
+title: Finnish XLMRobertaForTokenClassification Base Cased model (from tner)
+author: John Snow Labs
+name: xlmroberta_ner_base_fin
+date: 2024-09-07
+tags: [fi, open_source, xlm_roberta, ner, onnx]
+task: Named Entity Recognition
+language: fi
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-fin` is a Finnish model originally trained by `tner`.
+
+## Predicted Entities
+
+`other`, `person`, `location`, `organization`
+
+{:.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/xlmroberta_ner_base_fin_fi_5.5.0_3.0_1725687822122.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_fin_fi_5.5.0_3.0_1725687822122.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
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_base_fin","fi") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+ner_converter = NerConverter()\
+    .setInputCols(["document", "token", "ner"])\
+    .setOutputCol("ner_chunk")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+      .setInputCols(Array("text"))
+      .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_base_fin","fi")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val ner_converter = new NerConverter()
+    .setInputCols(Array("document", "token', "ner"))
+    .setOutputCol("ner_chunk")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("fi.ner.xlmr_roberta.base").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_base_fin|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|fi|
+|Size:|773.1 MB|
+
+## References
+
+References
+
+- https://huggingface.co/tner/xlm-roberta-base-fin
+- https://github.com/asahi417/tner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-xlmroberta_ner_base_finetuned_naija_finetuned_naija_pcm.md b/docs/_posts/ahmedlone127/2024-09-07-xlmroberta_ner_base_finetuned_naija_finetuned_naija_pcm.md
new file mode 100644
index 00000000000000..282d3599807b71
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-xlmroberta_ner_base_finetuned_naija_finetuned_naija_pcm.md
@@ -0,0 +1,120 @@
+---
+layout: model
+title: Nigerian Pidgin XLMRobertaForTokenClassification Base Cased model (from mbeukman)
+author: John Snow Labs
+name: xlmroberta_ner_base_finetuned_naija_finetuned_naija
+date: 2024-09-07
+tags: [pcm, open_source, xlm_roberta, ner, onnx]
+task: Named Entity Recognition
+language: pcm
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-naija-finetuned-ner-naija` is a Nigerian Pidgin model originally trained by `mbeukman`.
+
+## Predicted Entities
+
+`ORG`, `LOC`, `PER`, `DATE`
+
+{:.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/xlmroberta_ner_base_finetuned_naija_finetuned_naija_pcm_5.5.0_3.0_1725687806382.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_naija_finetuned_naija_pcm_5.5.0_3.0_1725687806382.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
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_base_finetuned_naija_finetuned_naija","pcm") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+ner_converter = NerConverter()\
+    .setInputCols(["document", "token", "ner"])\
+    .setOutputCol("ner_chunk")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+      .setInputCols(Array("text"))
+      .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_base_finetuned_naija_finetuned_naija","pcm")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val ner_converter = new NerConverter()
+    .setInputCols(Array("document", "token', "ner"))
+    .setOutputCol("ner_chunk")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("pcm.ner.xlmr_roberta.base_finetuned_naija.by_mbeukman").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_base_finetuned_naija_finetuned_naija|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|pcm|
+|Size:|1.0 GB|
+
+## References
+
+References
+
+- https://huggingface.co/mbeukman/xlm-roberta-base-finetuned-naija-finetuned-ner-naija
+- https://arxiv.org/abs/2103.11811
+- https://github.com/Michael-Beukman/NERTransfer
+- https://www.apache.org/licenses/LICENSE-2.0
+- https://github.com/Michael-Beukman/NERTransfer
+- https://github.com/masakhane-io/masakhane-ner
+- https://arxiv.org/pdf/2103.11811.pdf
+- https://arxiv.org/abs/2103.11811
+- https://arxiv.org/abs/2103.11811
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-xlmroberta_ner_base_finetuned_naija_finetuned_naija_pipeline_pcm.md b/docs/_posts/ahmedlone127/2024-09-07-xlmroberta_ner_base_finetuned_naija_finetuned_naija_pipeline_pcm.md
new file mode 100644
index 00000000000000..7a344c8fc9f093
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-xlmroberta_ner_base_finetuned_naija_finetuned_naija_pipeline_pcm.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Nigerian Pidgin xlmroberta_ner_base_finetuned_naija_finetuned_naija_pipeline pipeline XlmRoBertaForTokenClassification from mbeukman
+author: John Snow Labs
+name: xlmroberta_ner_base_finetuned_naija_finetuned_naija_pipeline
+date: 2024-09-07
+tags: [pcm, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: pcm
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_base_finetuned_naija_finetuned_naija_pipeline` is a Nigerian Pidgin model originally trained by mbeukman.
+
+{:.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/xlmroberta_ner_base_finetuned_naija_finetuned_naija_pipeline_pcm_5.5.0_3.0_1725687855073.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_base_finetuned_naija_finetuned_naija_pipeline_pcm_5.5.0_3.0_1725687855073.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
+
+pipeline = PretrainedPipeline("xlmroberta_ner_base_finetuned_naija_finetuned_naija_pipeline", lang = "pcm")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_base_finetuned_naija_finetuned_naija_pipeline", lang = "pcm")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_base_finetuned_naija_finetuned_naija_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|pcm|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/mbeukman/xlm-roberta-base-finetuned-naija-finetuned-ner-naija
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-xlmroberta_ner_edwardjross_base_finetuned_panx_all_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-07-xlmroberta_ner_edwardjross_base_finetuned_panx_all_pipeline_xx.md
new file mode 100644
index 00000000000000..e682663056cf5c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-xlmroberta_ner_edwardjross_base_finetuned_panx_all_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual xlmroberta_ner_edwardjross_base_finetuned_panx_all_pipeline pipeline XlmRoBertaForTokenClassification from edwardjross
+author: John Snow Labs
+name: xlmroberta_ner_edwardjross_base_finetuned_panx_all_pipeline
+date: 2024-09-07
+tags: [xx, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_edwardjross_base_finetuned_panx_all_pipeline` is a Multilingual model originally trained by edwardjross.
+
+{:.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/xlmroberta_ner_edwardjross_base_finetuned_panx_all_pipeline_xx_5.5.0_3.0_1725688107952.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_edwardjross_base_finetuned_panx_all_pipeline_xx_5.5.0_3.0_1725688107952.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
+
+pipeline = PretrainedPipeline("xlmroberta_ner_edwardjross_base_finetuned_panx_all_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_edwardjross_base_finetuned_panx_all_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_edwardjross_base_finetuned_panx_all_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|862.0 MB|
+
+## References
+
+https://huggingface.co/edwardjross/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-xlmroberta_ner_rgl73_base_finetuned_panx_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-07-xlmroberta_ner_rgl73_base_finetuned_panx_pipeline_de.md
new file mode 100644
index 00000000000000..5a7dc3515f4314
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-xlmroberta_ner_rgl73_base_finetuned_panx_pipeline_de.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: German xlmroberta_ner_rgl73_base_finetuned_panx_pipeline pipeline XlmRoBertaForTokenClassification from Rgl73
+author: John Snow Labs
+name: xlmroberta_ner_rgl73_base_finetuned_panx_pipeline
+date: 2024-09-07
+tags: [de, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_rgl73_base_finetuned_panx_pipeline` is a German model originally trained by Rgl73.
+
+{:.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/xlmroberta_ner_rgl73_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725687627057.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_rgl73_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725687627057.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
+
+pipeline = PretrainedPipeline("xlmroberta_ner_rgl73_base_finetuned_panx_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_rgl73_base_finetuned_panx_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_rgl73_base_finetuned_panx_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|853.4 MB|
+
+## References
+
+https://huggingface.co/Rgl73/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-xlmroberta_ner_tner_base_ontonotes5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-07-xlmroberta_ner_tner_base_ontonotes5_pipeline_en.md
new file mode 100644
index 00000000000000..ab2f8f1bb3ec80
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-xlmroberta_ner_tner_base_ontonotes5_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlmroberta_ner_tner_base_ontonotes5_pipeline pipeline XlmRoBertaForTokenClassification from asahi417
+author: John Snow Labs
+name: xlmroberta_ner_tner_base_ontonotes5_pipeline
+date: 2024-09-07
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_tner_base_ontonotes5_pipeline` is a English model originally trained by asahi417.
+
+{:.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/xlmroberta_ner_tner_base_ontonotes5_pipeline_en_5.5.0_3.0_1725689146328.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_tner_base_ontonotes5_pipeline_en_5.5.0_3.0_1725689146328.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
+
+pipeline = PretrainedPipeline("xlmroberta_ner_tner_base_ontonotes5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_tner_base_ontonotes5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_tner_base_ontonotes5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|798.0 MB|
+
+## References
+
+https://huggingface.co/asahi417/tner-xlm-roberta-base-ontonotes5
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-07-xy_en.md b/docs/_posts/ahmedlone127/2024-09-07-xy_en.md
new file mode 100644
index 00000000000000..c56a58df1c1f36
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-07-xy_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English xy DistilBertForQuestionAnswering from XuYiLX
+author: John Snow Labs
+name: xy
+date: 2024-09-07
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xy` is a English model originally trained by XuYiLX.
+
+{:.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/xy_en_5.5.0_3.0_1725735711942.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xy_en_5.5.0_3.0_1725735711942.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("xy","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("xy", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xy|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/XuYiLX/Xy
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-16_shot_twitter_2classes_en.md b/docs/_posts/ahmedlone127/2024-09-08-16_shot_twitter_2classes_en.md
new file mode 100644
index 00000000000000..674b0e0e097731
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-16_shot_twitter_2classes_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English 16_shot_twitter_2classes MPNetEmbeddings from Nhat1904
+author: John Snow Labs
+name: 16_shot_twitter_2classes
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`16_shot_twitter_2classes` is a English model originally trained by Nhat1904.
+
+{:.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/16_shot_twitter_2classes_en_5.5.0_3.0_1725815667362.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/16_shot_twitter_2classes_en_5.5.0_3.0_1725815667362.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("16_shot_twitter_2classes","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("16_shot_twitter_2classes","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|16_shot_twitter_2classes|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/Nhat1904/16-shot-twitter-2classes
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-579_stmodel_brand_rem_v5_en.md b/docs/_posts/ahmedlone127/2024-09-08-579_stmodel_brand_rem_v5_en.md
new file mode 100644
index 00000000000000..881fa868ea4321
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-579_stmodel_brand_rem_v5_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English 579_stmodel_brand_rem_v5 MPNetEmbeddings from jamiehudson
+author: John Snow Labs
+name: 579_stmodel_brand_rem_v5
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`579_stmodel_brand_rem_v5` is a English model originally trained by jamiehudson.
+
+{:.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/579_stmodel_brand_rem_v5_en_5.5.0_3.0_1725817251596.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/579_stmodel_brand_rem_v5_en_5.5.0_3.0_1725817251596.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("579_stmodel_brand_rem_v5","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("579_stmodel_brand_rem_v5","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|579_stmodel_brand_rem_v5|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/jamiehudson/579-STmodel-brand-rem-v5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-579_stmodel_v1a_en.md b/docs/_posts/ahmedlone127/2024-09-08-579_stmodel_v1a_en.md
new file mode 100644
index 00000000000000..a1d112013b8352
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-579_stmodel_v1a_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English 579_stmodel_v1a MPNetEmbeddings from jamiehudson
+author: John Snow Labs
+name: 579_stmodel_v1a
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`579_stmodel_v1a` is a English model originally trained by jamiehudson.
+
+{:.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/579_stmodel_v1a_en_5.5.0_3.0_1725815239659.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/579_stmodel_v1a_en_5.5.0_3.0_1725815239659.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("579_stmodel_v1a","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("579_stmodel_v1a","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|579_stmodel_v1a|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/jamiehudson/579-STmodel-v1a
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-579_stmodel_v1a_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-579_stmodel_v1a_pipeline_en.md
new file mode 100644
index 00000000000000..fcfae3ccd5734e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-579_stmodel_v1a_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English 579_stmodel_v1a_pipeline pipeline MPNetEmbeddings from jamiehudson
+author: John Snow Labs
+name: 579_stmodel_v1a_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`579_stmodel_v1a_pipeline` is a English model originally trained by jamiehudson.
+
+{:.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/579_stmodel_v1a_pipeline_en_5.5.0_3.0_1725815260726.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/579_stmodel_v1a_pipeline_en_5.5.0_3.0_1725815260726.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
+
+pipeline = PretrainedPipeline("579_stmodel_v1a_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("579_stmodel_v1a_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|579_stmodel_v1a_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/jamiehudson/579-STmodel-v1a
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-64data_en.md b/docs/_posts/ahmedlone127/2024-09-08-64data_en.md
new file mode 100644
index 00000000000000..b3102a405088be
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-64data_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English 64data MPNetEmbeddings from Watwat100
+author: John Snow Labs
+name: 64data
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`64data` is a English model originally trained by Watwat100.
+
+{:.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/64data_en_5.5.0_3.0_1725769184264.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/64data_en_5.5.0_3.0_1725769184264.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("64data","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("64data","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|64data|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/Watwat100/64data
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-acrossapps_ndd_mrbs_test_content_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-acrossapps_ndd_mrbs_test_content_pipeline_en.md
new file mode 100644
index 00000000000000..39e800331d8b03
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-acrossapps_ndd_mrbs_test_content_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English acrossapps_ndd_mrbs_test_content_pipeline pipeline DistilBertForSequenceClassification from lgk03
+author: John Snow Labs
+name: acrossapps_ndd_mrbs_test_content_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`acrossapps_ndd_mrbs_test_content_pipeline` is a English model originally trained by lgk03.
+
+{:.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/acrossapps_ndd_mrbs_test_content_pipeline_en_5.5.0_3.0_1725775315807.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/acrossapps_ndd_mrbs_test_content_pipeline_en_5.5.0_3.0_1725775315807.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
+
+pipeline = PretrainedPipeline("acrossapps_ndd_mrbs_test_content_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("acrossapps_ndd_mrbs_test_content_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|acrossapps_ndd_mrbs_test_content_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lgk03/ACROSSAPPS_NDD-mrbs_test-content
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-adapmit_multilabel_climatebert_f_en.md b/docs/_posts/ahmedlone127/2024-09-08-adapmit_multilabel_climatebert_f_en.md
new file mode 100644
index 00000000000000..f25320deec664e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-adapmit_multilabel_climatebert_f_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English adapmit_multilabel_climatebert_f RoBertaForSequenceClassification from GIZ
+author: John Snow Labs
+name: adapmit_multilabel_climatebert_f
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`adapmit_multilabel_climatebert_f` is a English model originally trained by GIZ.
+
+{:.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/adapmit_multilabel_climatebert_f_en_5.5.0_3.0_1725830075381.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/adapmit_multilabel_climatebert_f_en_5.5.0_3.0_1725830075381.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("adapmit_multilabel_climatebert_f","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("adapmit_multilabel_climatebert_f", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|adapmit_multilabel_climatebert_f|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|309.6 MB|
+
+## References
+
+https://huggingface.co/GIZ/ADAPMIT-multilabel-climatebert_f
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-adapmit_multilabel_climatebert_f_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-adapmit_multilabel_climatebert_f_pipeline_en.md
new file mode 100644
index 00000000000000..3af2cf31a8bb57
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-adapmit_multilabel_climatebert_f_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English adapmit_multilabel_climatebert_f_pipeline pipeline RoBertaForSequenceClassification from GIZ
+author: John Snow Labs
+name: adapmit_multilabel_climatebert_f_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`adapmit_multilabel_climatebert_f_pipeline` is a English model originally trained by GIZ.
+
+{:.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/adapmit_multilabel_climatebert_f_pipeline_en_5.5.0_3.0_1725830090823.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/adapmit_multilabel_climatebert_f_pipeline_en_5.5.0_3.0_1725830090823.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
+
+pipeline = PretrainedPipeline("adapmit_multilabel_climatebert_f_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("adapmit_multilabel_climatebert_f_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|adapmit_multilabel_climatebert_f_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|309.7 MB|
+
+## References
+
+https://huggingface.co/GIZ/ADAPMIT-multilabel-climatebert_f
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-afro_xlmr_base_igbo_5e_5_en.md b/docs/_posts/ahmedlone127/2024-09-08-afro_xlmr_base_igbo_5e_5_en.md
new file mode 100644
index 00000000000000..e64ba913cece8e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-afro_xlmr_base_igbo_5e_5_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English afro_xlmr_base_igbo_5e_5 XlmRoBertaForTokenClassification from grace-pro
+author: John Snow Labs
+name: afro_xlmr_base_igbo_5e_5
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`afro_xlmr_base_igbo_5e_5` is a English model originally trained by grace-pro.
+
+{:.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/afro_xlmr_base_igbo_5e_5_en_5.5.0_3.0_1725806434802.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/afro_xlmr_base_igbo_5e_5_en_5.5.0_3.0_1725806434802.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("afro_xlmr_base_igbo_5e_5","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("afro_xlmr_base_igbo_5e_5", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|afro_xlmr_base_igbo_5e_5|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/grace-pro/afro-xlmr-base-igbo-5e-5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-afro_xlmr_base_igbo_5e_5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-afro_xlmr_base_igbo_5e_5_pipeline_en.md
new file mode 100644
index 00000000000000..2520b5a5cfd8c6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-afro_xlmr_base_igbo_5e_5_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English afro_xlmr_base_igbo_5e_5_pipeline pipeline XlmRoBertaForTokenClassification from grace-pro
+author: John Snow Labs
+name: afro_xlmr_base_igbo_5e_5_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`afro_xlmr_base_igbo_5e_5_pipeline` is a English model originally trained by grace-pro.
+
+{:.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/afro_xlmr_base_igbo_5e_5_pipeline_en_5.5.0_3.0_1725806488228.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/afro_xlmr_base_igbo_5e_5_pipeline_en_5.5.0_3.0_1725806488228.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
+
+pipeline = PretrainedPipeline("afro_xlmr_base_igbo_5e_5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("afro_xlmr_base_igbo_5e_5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|afro_xlmr_base_igbo_5e_5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/grace-pro/afro-xlmr-base-igbo-5e-5
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-afro_xlmr_mini_finetuned_hausa_en.md b/docs/_posts/ahmedlone127/2024-09-08-afro_xlmr_mini_finetuned_hausa_en.md
new file mode 100644
index 00000000000000..de071600c01752
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-afro_xlmr_mini_finetuned_hausa_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English afro_xlmr_mini_finetuned_hausa XlmRoBertaForTokenClassification from grace-pro
+author: John Snow Labs
+name: afro_xlmr_mini_finetuned_hausa
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`afro_xlmr_mini_finetuned_hausa` is a English model originally trained by grace-pro.
+
+{:.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/afro_xlmr_mini_finetuned_hausa_en_5.5.0_3.0_1725783910322.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/afro_xlmr_mini_finetuned_hausa_en_5.5.0_3.0_1725783910322.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("afro_xlmr_mini_finetuned_hausa","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("afro_xlmr_mini_finetuned_hausa", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|afro_xlmr_mini_finetuned_hausa|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|443.1 MB|
+
+## References
+
+https://huggingface.co/grace-pro/afro-xlmr-mini-finetuned-hausa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-afro_xlmr_mini_finetuned_hausa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-afro_xlmr_mini_finetuned_hausa_pipeline_en.md
new file mode 100644
index 00000000000000..1c13a367295c7d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-afro_xlmr_mini_finetuned_hausa_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English afro_xlmr_mini_finetuned_hausa_pipeline pipeline XlmRoBertaForTokenClassification from grace-pro
+author: John Snow Labs
+name: afro_xlmr_mini_finetuned_hausa_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`afro_xlmr_mini_finetuned_hausa_pipeline` is a English model originally trained by grace-pro.
+
+{:.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/afro_xlmr_mini_finetuned_hausa_pipeline_en_5.5.0_3.0_1725783930566.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/afro_xlmr_mini_finetuned_hausa_pipeline_en_5.5.0_3.0_1725783930566.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
+
+pipeline = PretrainedPipeline("afro_xlmr_mini_finetuned_hausa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("afro_xlmr_mini_finetuned_hausa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|afro_xlmr_mini_finetuned_hausa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|443.1 MB|
+
+## References
+
+https://huggingface.co/grace-pro/afro-xlmr-mini-finetuned-hausa
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-ai_club_inductions_21_nlp_distilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-ai_club_inductions_21_nlp_distilbert_pipeline_en.md
new file mode 100644
index 00000000000000..d5d4c4169dba05
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-ai_club_inductions_21_nlp_distilbert_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ai_club_inductions_21_nlp_distilbert_pipeline pipeline DistilBertForQuestionAnswering from AyushPJ
+author: John Snow Labs
+name: ai_club_inductions_21_nlp_distilbert_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ai_club_inductions_21_nlp_distilbert_pipeline` is a English model originally trained by AyushPJ.
+
+{:.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/ai_club_inductions_21_nlp_distilbert_pipeline_en_5.5.0_3.0_1725798560299.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ai_club_inductions_21_nlp_distilbert_pipeline_en_5.5.0_3.0_1725798560299.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
+
+pipeline = PretrainedPipeline("ai_club_inductions_21_nlp_distilbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ai_club_inductions_21_nlp_distilbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ai_club_inductions_21_nlp_distilbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/AyushPJ/ai-club-inductions-21-nlp-distilBERT
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-albert_base_chinese_0407_ner_en.md b/docs/_posts/ahmedlone127/2024-09-08-albert_base_chinese_0407_ner_en.md
new file mode 100644
index 00000000000000..02151d66d5373e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-albert_base_chinese_0407_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English albert_base_chinese_0407_ner BertForTokenClassification from yihsuan
+author: John Snow Labs
+name: albert_base_chinese_0407_ner
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_chinese_0407_ner` is a English model originally trained by yihsuan.
+
+{:.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/albert_base_chinese_0407_ner_en_5.5.0_3.0_1725834641944.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_chinese_0407_ner_en_5.5.0_3.0_1725834641944.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("albert_base_chinese_0407_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("albert_base_chinese_0407_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_chinese_0407_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|37.6 MB|
+
+## References
+
+https://huggingface.co/yihsuan/albert-base-chinese-0407-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-albert_base_chinese_0407_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-albert_base_chinese_0407_ner_pipeline_en.md
new file mode 100644
index 00000000000000..3ff6d1c1d336a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-albert_base_chinese_0407_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English albert_base_chinese_0407_ner_pipeline pipeline BertForTokenClassification from yihsuan
+author: John Snow Labs
+name: albert_base_chinese_0407_ner_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_chinese_0407_ner_pipeline` is a English model originally trained by yihsuan.
+
+{:.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/albert_base_chinese_0407_ner_pipeline_en_5.5.0_3.0_1725834644246.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_chinese_0407_ner_pipeline_en_5.5.0_3.0_1725834644246.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
+
+pipeline = PretrainedPipeline("albert_base_chinese_0407_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("albert_base_chinese_0407_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_base_chinese_0407_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|37.6 MB|
+
+## References
+
+https://huggingface.co/yihsuan/albert-base-chinese-0407-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-albert_model__29_1_en.md b/docs/_posts/ahmedlone127/2024-09-08-albert_model__29_1_en.md
new file mode 100644
index 00000000000000..1e012f118e0731
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-albert_model__29_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English albert_model__29_1 DistilBertForSequenceClassification from KalaiselvanD
+author: John Snow Labs
+name: albert_model__29_1
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_model__29_1` is a English model originally trained by KalaiselvanD.
+
+{:.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/albert_model__29_1_en_5.5.0_3.0_1725764280072.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_model__29_1_en_5.5.0_3.0_1725764280072.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("albert_model__29_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("albert_model__29_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_model__29_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/KalaiselvanD/albert_model__29_1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_128_20_mnr_en.md b/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_128_20_mnr_en.md
new file mode 100644
index 00000000000000..9bda44d2095afa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_128_20_mnr_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English all_mpnet_base_128_20_mnr MPNetEmbeddings from ronanki
+author: John Snow Labs
+name: all_mpnet_base_128_20_mnr
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`all_mpnet_base_128_20_mnr` is a English model originally trained by ronanki.
+
+{:.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/all_mpnet_base_128_20_mnr_en_5.5.0_3.0_1725815726032.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_128_20_mnr_en_5.5.0_3.0_1725815726032.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_128_20_mnr","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_128_20_mnr","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_mpnet_base_128_20_mnr|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/ronanki/all_mpnet_base_128_20_MNR
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_128_20_mnr_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_128_20_mnr_pipeline_en.md
new file mode 100644
index 00000000000000..4fb1d05b313ded
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_128_20_mnr_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English all_mpnet_base_128_20_mnr_pipeline pipeline MPNetEmbeddings from ronanki
+author: John Snow Labs
+name: all_mpnet_base_128_20_mnr_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_128_20_mnr_pipeline` is a English model originally trained by ronanki.
+
+{:.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/all_mpnet_base_128_20_mnr_pipeline_en_5.5.0_3.0_1725815747505.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_128_20_mnr_pipeline_en_5.5.0_3.0_1725815747505.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
+
+pipeline = PretrainedPipeline("all_mpnet_base_128_20_mnr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_mpnet_base_128_20_mnr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_mpnet_base_128_20_mnr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/ronanki/all_mpnet_base_128_20_MNR
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_newtriplets_v2_lr_1e_8_m_5_e_3_en.md b/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_newtriplets_v2_lr_1e_8_m_5_e_3_en.md
new file mode 100644
index 00000000000000..80a92bcf2a2988
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_newtriplets_v2_lr_1e_8_m_5_e_3_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English all_mpnet_base_newtriplets_v2_lr_1e_8_m_5_e_3 MPNetEmbeddings from luiz-and-robert-thesis
+author: John Snow Labs
+name: all_mpnet_base_newtriplets_v2_lr_1e_8_m_5_e_3
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`all_mpnet_base_newtriplets_v2_lr_1e_8_m_5_e_3` is a English model originally trained by luiz-and-robert-thesis.
+
+{:.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/all_mpnet_base_newtriplets_v2_lr_1e_8_m_5_e_3_en_5.5.0_3.0_1725817107931.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_newtriplets_v2_lr_1e_8_m_5_e_3_en_5.5.0_3.0_1725817107931.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_newtriplets_v2_lr_1e_8_m_5_e_3","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_newtriplets_v2_lr_1e_8_m_5_e_3","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_mpnet_base_newtriplets_v2_lr_1e_8_m_5_e_3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/luiz-and-robert-thesis/all-mpnet-base-newtriplets-v2-lr-1e-8-m-5-e-3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_2epoch_100pair_mar2_closs_morl_en.md b/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_2epoch_100pair_mar2_closs_morl_en.md
new file mode 100644
index 00000000000000..0262ea5803712e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_2epoch_100pair_mar2_closs_morl_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English all_mpnet_base_v2_2epoch_100pair_mar2_closs_morl MPNetEmbeddings from ahessamb
+author: John Snow Labs
+name: all_mpnet_base_v2_2epoch_100pair_mar2_closs_morl
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`all_mpnet_base_v2_2epoch_100pair_mar2_closs_morl` is a English model originally trained by ahessamb.
+
+{:.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/all_mpnet_base_v2_2epoch_100pair_mar2_closs_morl_en_5.5.0_3.0_1725815612638.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_2epoch_100pair_mar2_closs_morl_en_5.5.0_3.0_1725815612638.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_v2_2epoch_100pair_mar2_closs_morl","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_v2_2epoch_100pair_mar2_closs_morl","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_mpnet_base_v2_2epoch_100pair_mar2_closs_morl|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/ahessamb/all-mpnet-base-v2-2epoch-100pair-mar2-closs-morl
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_2epoch_100pair_mar2_closs_morl_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_2epoch_100pair_mar2_closs_morl_pipeline_en.md
new file mode 100644
index 00000000000000..9916cfc2203f0b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_2epoch_100pair_mar2_closs_morl_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English all_mpnet_base_v2_2epoch_100pair_mar2_closs_morl_pipeline pipeline MPNetEmbeddings from ahessamb
+author: John Snow Labs
+name: all_mpnet_base_v2_2epoch_100pair_mar2_closs_morl_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_2epoch_100pair_mar2_closs_morl_pipeline` is a English model originally trained by ahessamb.
+
+{:.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/all_mpnet_base_v2_2epoch_100pair_mar2_closs_morl_pipeline_en_5.5.0_3.0_1725815634274.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_2epoch_100pair_mar2_closs_morl_pipeline_en_5.5.0_3.0_1725815634274.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
+
+pipeline = PretrainedPipeline("all_mpnet_base_v2_2epoch_100pair_mar2_closs_morl_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_mpnet_base_v2_2epoch_100pair_mar2_closs_morl_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_mpnet_base_v2_2epoch_100pair_mar2_closs_morl_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/ahessamb/all-mpnet-base-v2-2epoch-100pair-mar2-closs-morl
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_akshitguptafintek24_en.md b/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_akshitguptafintek24_en.md
new file mode 100644
index 00000000000000..895d98a9a7a421
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_akshitguptafintek24_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English all_mpnet_base_v2_akshitguptafintek24 MPNetEmbeddings from akshitguptafintek24
+author: John Snow Labs
+name: all_mpnet_base_v2_akshitguptafintek24
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`all_mpnet_base_v2_akshitguptafintek24` is a English model originally trained by akshitguptafintek24.
+
+{:.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/all_mpnet_base_v2_akshitguptafintek24_en_5.5.0_3.0_1725815386716.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_akshitguptafintek24_en_5.5.0_3.0_1725815386716.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_v2_akshitguptafintek24","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_v2_akshitguptafintek24","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_mpnet_base_v2_akshitguptafintek24|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/akshitguptafintek24/all-mpnet-base-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_bioasq_1epoch_batch32_100steps_en.md b/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_bioasq_1epoch_batch32_100steps_en.md
new file mode 100644
index 00000000000000..b6db989573b23b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_bioasq_1epoch_batch32_100steps_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English all_mpnet_base_v2_bioasq_1epoch_batch32_100steps MPNetEmbeddings from juanpablomesa
+author: John Snow Labs
+name: all_mpnet_base_v2_bioasq_1epoch_batch32_100steps
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`all_mpnet_base_v2_bioasq_1epoch_batch32_100steps` is a English model originally trained by juanpablomesa.
+
+{:.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/all_mpnet_base_v2_bioasq_1epoch_batch32_100steps_en_5.5.0_3.0_1725816853316.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_bioasq_1epoch_batch32_100steps_en_5.5.0_3.0_1725816853316.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_v2_bioasq_1epoch_batch32_100steps","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_v2_bioasq_1epoch_batch32_100steps","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_mpnet_base_v2_bioasq_1epoch_batch32_100steps|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/juanpablomesa/all-mpnet-base-v2-bioasq-1epoch-batch32-100steps
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_eclass_jobeer_en.md b/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_eclass_jobeer_en.md
new file mode 100644
index 00000000000000..e48d3472c290e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_eclass_jobeer_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English all_mpnet_base_v2_eclass_jobeer MPNetEmbeddings from JoBeer
+author: John Snow Labs
+name: all_mpnet_base_v2_eclass_jobeer
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`all_mpnet_base_v2_eclass_jobeer` is a English model originally trained by JoBeer.
+
+{:.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/all_mpnet_base_v2_eclass_jobeer_en_5.5.0_3.0_1725815114038.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_eclass_jobeer_en_5.5.0_3.0_1725815114038.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_v2_eclass_jobeer","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_v2_eclass_jobeer","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_mpnet_base_v2_eclass_jobeer|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/JoBeer/all-mpnet-base-v2-eclass
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_eclass_jobeer_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_eclass_jobeer_pipeline_en.md
new file mode 100644
index 00000000000000..6016a4550c6fb7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_eclass_jobeer_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English all_mpnet_base_v2_eclass_jobeer_pipeline pipeline MPNetEmbeddings from JoBeer
+author: John Snow Labs
+name: all_mpnet_base_v2_eclass_jobeer_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_eclass_jobeer_pipeline` is a English model originally trained by JoBeer.
+
+{:.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/all_mpnet_base_v2_eclass_jobeer_pipeline_en_5.5.0_3.0_1725815141414.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_eclass_jobeer_pipeline_en_5.5.0_3.0_1725815141414.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
+
+pipeline = PretrainedPipeline("all_mpnet_base_v2_eclass_jobeer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_mpnet_base_v2_eclass_jobeer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_mpnet_base_v2_eclass_jobeer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/JoBeer/all-mpnet-base-v2-eclass
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..2f519cd0d07f88
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_finetuned_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English all_mpnet_base_v2_finetuned_pipeline pipeline MPNetEmbeddings from DashReza7
+author: John Snow Labs
+name: all_mpnet_base_v2_finetuned_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_finetuned_pipeline` is a English model originally trained by DashReza7.
+
+{:.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/all_mpnet_base_v2_finetuned_pipeline_en_5.5.0_3.0_1725816725918.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_finetuned_pipeline_en_5.5.0_3.0_1725816725918.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
+
+pipeline = PretrainedPipeline("all_mpnet_base_v2_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_mpnet_base_v2_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_mpnet_base_v2_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/DashReza7/all-mpnet-base-v2_FINETUNED
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_margin_5_epoch_1_en.md b/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_margin_5_epoch_1_en.md
new file mode 100644
index 00000000000000..42bc93b7512804
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_margin_5_epoch_1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English all_mpnet_base_v2_margin_5_epoch_1 MPNetEmbeddings from luiz-and-robert-thesis
+author: John Snow Labs
+name: all_mpnet_base_v2_margin_5_epoch_1
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`all_mpnet_base_v2_margin_5_epoch_1` is a English model originally trained by luiz-and-robert-thesis.
+
+{:.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/all_mpnet_base_v2_margin_5_epoch_1_en_5.5.0_3.0_1725815935445.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_margin_5_epoch_1_en_5.5.0_3.0_1725815935445.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_v2_margin_5_epoch_1","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_v2_margin_5_epoch_1","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_mpnet_base_v2_margin_5_epoch_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/luiz-and-robert-thesis/all-mpnet-base-v2-margin-5-epoch-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_navteca_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_navteca_pipeline_en.md
new file mode 100644
index 00000000000000..ffa365cba10c54
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_navteca_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English all_mpnet_base_v2_navteca_pipeline pipeline MPNetEmbeddings from navteca
+author: John Snow Labs
+name: all_mpnet_base_v2_navteca_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_navteca_pipeline` is a English model originally trained by navteca.
+
+{:.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/all_mpnet_base_v2_navteca_pipeline_en_5.5.0_3.0_1725769334709.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_navteca_pipeline_en_5.5.0_3.0_1725769334709.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
+
+pipeline = PretrainedPipeline("all_mpnet_base_v2_navteca_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_mpnet_base_v2_navteca_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_mpnet_base_v2_navteca_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/navteca/all-mpnet-base-v2
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_topic_abstract_similarity_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_topic_abstract_similarity_pipeline_en.md
new file mode 100644
index 00000000000000..6a649778005e5f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_topic_abstract_similarity_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English all_mpnet_base_v2_topic_abstract_similarity_pipeline pipeline MPNetEmbeddings from Eitanli
+author: John Snow Labs
+name: all_mpnet_base_v2_topic_abstract_similarity_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_topic_abstract_similarity_pipeline` is a English model originally trained by Eitanli.
+
+{:.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/all_mpnet_base_v2_topic_abstract_similarity_pipeline_en_5.5.0_3.0_1725769346679.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_topic_abstract_similarity_pipeline_en_5.5.0_3.0_1725769346679.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
+
+pipeline = PretrainedPipeline("all_mpnet_base_v2_topic_abstract_similarity_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_mpnet_base_v2_topic_abstract_similarity_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_mpnet_base_v2_topic_abstract_similarity_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/Eitanli/all-mpnet-base-v2-topic-abstract-similarity
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_topic_abstract_similarity_v2_eitanli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_topic_abstract_similarity_v2_eitanli_pipeline_en.md
new file mode 100644
index 00000000000000..f17ef18b61ba85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-all_mpnet_base_v2_topic_abstract_similarity_v2_eitanli_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English all_mpnet_base_v2_topic_abstract_similarity_v2_eitanli_pipeline pipeline MPNetEmbeddings from Eitanli
+author: John Snow Labs
+name: all_mpnet_base_v2_topic_abstract_similarity_v2_eitanli_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_topic_abstract_similarity_v2_eitanli_pipeline` is a English model originally trained by Eitanli.
+
+{:.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/all_mpnet_base_v2_topic_abstract_similarity_v2_eitanli_pipeline_en_5.5.0_3.0_1725769908072.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_topic_abstract_similarity_v2_eitanli_pipeline_en_5.5.0_3.0_1725769908072.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
+
+pipeline = PretrainedPipeline("all_mpnet_base_v2_topic_abstract_similarity_v2_eitanli_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_mpnet_base_v2_topic_abstract_similarity_v2_eitanli_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_mpnet_base_v2_topic_abstract_similarity_v2_eitanli_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/Eitanli/all-mpnet-base-v2-topic-abstract-similarity-v2
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-all_roberta_large_v1_meta_4_16_5_oos_en.md b/docs/_posts/ahmedlone127/2024-09-08-all_roberta_large_v1_meta_4_16_5_oos_en.md
new file mode 100644
index 00000000000000..024e69f0b5ecd6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-all_roberta_large_v1_meta_4_16_5_oos_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English all_roberta_large_v1_meta_4_16_5_oos RoBertaForSequenceClassification from fathyshalab
+author: John Snow Labs
+name: all_roberta_large_v1_meta_4_16_5_oos
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_roberta_large_v1_meta_4_16_5_oos` is a English model originally trained by fathyshalab.
+
+{:.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/all_roberta_large_v1_meta_4_16_5_oos_en_5.5.0_3.0_1725830200215.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_roberta_large_v1_meta_4_16_5_oos_en_5.5.0_3.0_1725830200215.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("all_roberta_large_v1_meta_4_16_5_oos","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("all_roberta_large_v1_meta_4_16_5_oos", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_roberta_large_v1_meta_4_16_5_oos|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/fathyshalab/all-roberta-large-v1-meta-4-16-5-oos
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-amazonpolarity_fewshot_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-amazonpolarity_fewshot_pipeline_en.md
new file mode 100644
index 00000000000000..0cba532ac050ea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-amazonpolarity_fewshot_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English amazonpolarity_fewshot_pipeline pipeline MPNetEmbeddings from pig4431
+author: John Snow Labs
+name: amazonpolarity_fewshot_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`amazonpolarity_fewshot_pipeline` is a English model originally trained by pig4431.
+
+{:.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/amazonpolarity_fewshot_pipeline_en_5.5.0_3.0_1725770090398.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/amazonpolarity_fewshot_pipeline_en_5.5.0_3.0_1725770090398.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
+
+pipeline = PretrainedPipeline("amazonpolarity_fewshot_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("amazonpolarity_fewshot_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|amazonpolarity_fewshot_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.0 MB|
+
+## References
+
+https://huggingface.co/pig4431/amazonPolarity_fewshot
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-angela_shuffle_untranslated_eval_en.md b/docs/_posts/ahmedlone127/2024-09-08-angela_shuffle_untranslated_eval_en.md
new file mode 100644
index 00000000000000..95c1ce9dfa06c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-angela_shuffle_untranslated_eval_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English angela_shuffle_untranslated_eval XlmRoBertaForTokenClassification from azhang1212
+author: John Snow Labs
+name: angela_shuffle_untranslated_eval
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`angela_shuffle_untranslated_eval` is a English model originally trained by azhang1212.
+
+{:.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/angela_shuffle_untranslated_eval_en_5.5.0_3.0_1725774435179.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/angela_shuffle_untranslated_eval_en_5.5.0_3.0_1725774435179.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("angela_shuffle_untranslated_eval","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("angela_shuffle_untranslated_eval", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|angela_shuffle_untranslated_eval|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/azhang1212/angela_shuffle_untranslated_eval
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-angela_shuffle_untranslated_eval_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-angela_shuffle_untranslated_eval_pipeline_en.md
new file mode 100644
index 00000000000000..00b932dd6e5c76
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-angela_shuffle_untranslated_eval_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English angela_shuffle_untranslated_eval_pipeline pipeline XlmRoBertaForTokenClassification from azhang1212
+author: John Snow Labs
+name: angela_shuffle_untranslated_eval_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`angela_shuffle_untranslated_eval_pipeline` is a English model originally trained by azhang1212.
+
+{:.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/angela_shuffle_untranslated_eval_pipeline_en_5.5.0_3.0_1725774483814.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/angela_shuffle_untranslated_eval_pipeline_en_5.5.0_3.0_1725774483814.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
+
+pipeline = PretrainedPipeline("angela_shuffle_untranslated_eval_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("angela_shuffle_untranslated_eval_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|angela_shuffle_untranslated_eval_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/azhang1212/angela_shuffle_untranslated_eval
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-arabert_arabic_sentiment_analysis_ar.md b/docs/_posts/ahmedlone127/2024-09-08-arabert_arabic_sentiment_analysis_ar.md
new file mode 100644
index 00000000000000..beb08f0192a7ae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-arabert_arabic_sentiment_analysis_ar.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Arabic arabert_arabic_sentiment_analysis BertForSequenceClassification from PRAli22
+author: John Snow Labs
+name: arabert_arabic_sentiment_analysis
+date: 2024-09-08
+tags: [ar, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arabert_arabic_sentiment_analysis` is a Arabic model originally trained by PRAli22.
+
+{:.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/arabert_arabic_sentiment_analysis_ar_5.5.0_3.0_1725801943545.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arabert_arabic_sentiment_analysis_ar_5.5.0_3.0_1725801943545.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("arabert_arabic_sentiment_analysis","ar") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("arabert_arabic_sentiment_analysis", "ar")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|arabert_arabic_sentiment_analysis|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|ar|
+|Size:|507.3 MB|
+
+## References
+
+https://huggingface.co/PRAli22/AraBert-Arabic-Sentiment-Analysis
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-arabert_arabic_sentiment_analysis_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-08-arabert_arabic_sentiment_analysis_pipeline_ar.md
new file mode 100644
index 00000000000000..416b4c5e477bde
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-arabert_arabic_sentiment_analysis_pipeline_ar.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Arabic arabert_arabic_sentiment_analysis_pipeline pipeline BertForSequenceClassification from PRAli22
+author: John Snow Labs
+name: arabert_arabic_sentiment_analysis_pipeline
+date: 2024-09-08
+tags: [ar, open_source, pipeline, onnx]
+task: Text Classification
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arabert_arabic_sentiment_analysis_pipeline` is a Arabic model originally trained by PRAli22.
+
+{:.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/arabert_arabic_sentiment_analysis_pipeline_ar_5.5.0_3.0_1725801968479.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arabert_arabic_sentiment_analysis_pipeline_ar_5.5.0_3.0_1725801968479.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
+
+pipeline = PretrainedPipeline("arabert_arabic_sentiment_analysis_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("arabert_arabic_sentiment_analysis_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|arabert_arabic_sentiment_analysis_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|507.3 MB|
+
+## References
+
+https://huggingface.co/PRAli22/AraBert-Arabic-Sentiment-Analysis
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-arabert_base_algerian_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-08-arabert_base_algerian_pipeline_ar.md
new file mode 100644
index 00000000000000..98978fe6e1598f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-arabert_base_algerian_pipeline_ar.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Arabic arabert_base_algerian_pipeline pipeline BertForSequenceClassification from Abdou
+author: John Snow Labs
+name: arabert_base_algerian_pipeline
+date: 2024-09-08
+tags: [ar, open_source, pipeline, onnx]
+task: Text Classification
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arabert_base_algerian_pipeline` is a Arabic model originally trained by Abdou.
+
+{:.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/arabert_base_algerian_pipeline_ar_5.5.0_3.0_1725838894613.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arabert_base_algerian_pipeline_ar_5.5.0_3.0_1725838894613.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
+
+pipeline = PretrainedPipeline("arabert_base_algerian_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("arabert_base_algerian_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|arabert_base_algerian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|414.2 MB|
+
+## References
+
+https://huggingface.co/Abdou/arabert-base-algerian
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-arabic_english_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-arabic_english_model_pipeline_en.md
new file mode 100644
index 00000000000000..3cf8384b7e0eab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-arabic_english_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English arabic_english_model_pipeline pipeline MarianTransformer from BoghdadyJR
+author: John Snow Labs
+name: arabic_english_model_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arabic_english_model_pipeline` is a English model originally trained by BoghdadyJR.
+
+{:.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/arabic_english_model_pipeline_en_5.5.0_3.0_1725766051630.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arabic_english_model_pipeline_en_5.5.0_3.0_1725766051630.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
+
+pipeline = PretrainedPipeline("arabic_english_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("arabic_english_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|arabic_english_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|528.4 MB|
+
+## References
+
+https://huggingface.co/BoghdadyJR/ar-en-model
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-arabic_mpnet_base_all_nli_triplet_ar.md b/docs/_posts/ahmedlone127/2024-09-08-arabic_mpnet_base_all_nli_triplet_ar.md
new file mode 100644
index 00000000000000..876d097b8709a9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-arabic_mpnet_base_all_nli_triplet_ar.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Arabic arabic_mpnet_base_all_nli_triplet MPNetEmbeddings from Omartificial-Intelligence-Space
+author: John Snow Labs
+name: arabic_mpnet_base_all_nli_triplet
+date: 2024-09-08
+tags: [ar, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.0
+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.`arabic_mpnet_base_all_nli_triplet` is a Arabic model originally trained by Omartificial-Intelligence-Space.
+
+{:.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/arabic_mpnet_base_all_nli_triplet_ar_5.5.0_3.0_1725815498852.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arabic_mpnet_base_all_nli_triplet_ar_5.5.0_3.0_1725815498852.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("arabic_mpnet_base_all_nli_triplet","ar") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("arabic_mpnet_base_all_nli_triplet","ar") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|arabic_mpnet_base_all_nli_triplet|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|ar|
+|Size:|394.6 MB|
+
+## References
+
+https://huggingface.co/Omartificial-Intelligence-Space/Arabic-mpnet-base-all-nli-triplet
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-arabic_mpnet_base_all_nli_triplet_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-08-arabic_mpnet_base_all_nli_triplet_pipeline_ar.md
new file mode 100644
index 00000000000000..947f257499b629
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-arabic_mpnet_base_all_nli_triplet_pipeline_ar.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Arabic arabic_mpnet_base_all_nli_triplet_pipeline pipeline MPNetEmbeddings from Omartificial-Intelligence-Space
+author: John Snow Labs
+name: arabic_mpnet_base_all_nli_triplet_pipeline
+date: 2024-09-08
+tags: [ar, open_source, pipeline, onnx]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arabic_mpnet_base_all_nli_triplet_pipeline` is a Arabic model originally trained by Omartificial-Intelligence-Space.
+
+{:.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/arabic_mpnet_base_all_nli_triplet_pipeline_ar_5.5.0_3.0_1725815525263.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arabic_mpnet_base_all_nli_triplet_pipeline_ar_5.5.0_3.0_1725815525263.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
+
+pipeline = PretrainedPipeline("arabic_mpnet_base_all_nli_triplet_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("arabic_mpnet_base_all_nli_triplet_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|arabic_mpnet_base_all_nli_triplet_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|394.6 MB|
+
+## References
+
+https://huggingface.co/Omartificial-Intelligence-Space/Arabic-mpnet-base-all-nli-triplet
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-are_there_chronic_diseases_bert_first512_en.md b/docs/_posts/ahmedlone127/2024-09-08-are_there_chronic_diseases_bert_first512_en.md
new file mode 100644
index 00000000000000..f27a65d7887a4a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-are_there_chronic_diseases_bert_first512_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English are_there_chronic_diseases_bert_first512 BertForSequenceClassification from etadevosyan
+author: John Snow Labs
+name: are_there_chronic_diseases_bert_first512
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`are_there_chronic_diseases_bert_first512` is a English model originally trained by etadevosyan.
+
+{:.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/are_there_chronic_diseases_bert_first512_en_5.5.0_3.0_1725819140511.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/are_there_chronic_diseases_bert_first512_en_5.5.0_3.0_1725819140511.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("are_there_chronic_diseases_bert_first512","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("are_there_chronic_diseases_bert_first512", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|are_there_chronic_diseases_bert_first512|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|666.5 MB|
+
+## References
+
+https://huggingface.co/etadevosyan/are_there_chronic_diseases_bert_First512
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-are_there_chronic_diseases_bert_first512_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-are_there_chronic_diseases_bert_first512_pipeline_en.md
new file mode 100644
index 00000000000000..291a035c04a96e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-are_there_chronic_diseases_bert_first512_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English are_there_chronic_diseases_bert_first512_pipeline pipeline BertForSequenceClassification from etadevosyan
+author: John Snow Labs
+name: are_there_chronic_diseases_bert_first512_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`are_there_chronic_diseases_bert_first512_pipeline` is a English model originally trained by etadevosyan.
+
+{:.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/are_there_chronic_diseases_bert_first512_pipeline_en_5.5.0_3.0_1725819174317.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/are_there_chronic_diseases_bert_first512_pipeline_en_5.5.0_3.0_1725819174317.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
+
+pipeline = PretrainedPipeline("are_there_chronic_diseases_bert_first512_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("are_there_chronic_diseases_bert_first512_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|are_there_chronic_diseases_bert_first512_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|666.5 MB|
+
+## References
+
+https://huggingface.co/etadevosyan/are_there_chronic_diseases_bert_First512
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-are_there_harmful_habits_bert_mix128_en.md b/docs/_posts/ahmedlone127/2024-09-08-are_there_harmful_habits_bert_mix128_en.md
new file mode 100644
index 00000000000000..1ce505676d7e1d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-are_there_harmful_habits_bert_mix128_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English are_there_harmful_habits_bert_mix128 BertForSequenceClassification from etadevosyan
+author: John Snow Labs
+name: are_there_harmful_habits_bert_mix128
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`are_there_harmful_habits_bert_mix128` is a English model originally trained by etadevosyan.
+
+{:.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/are_there_harmful_habits_bert_mix128_en_5.5.0_3.0_1725819828613.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/are_there_harmful_habits_bert_mix128_en_5.5.0_3.0_1725819828613.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("are_there_harmful_habits_bert_mix128","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("are_there_harmful_habits_bert_mix128", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|are_there_harmful_habits_bert_mix128|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|666.5 MB|
+
+## References
+
+https://huggingface.co/etadevosyan/are_there_harmful_habits_bert_Mix128
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-argureviews_specificity_roberta_v1_en.md b/docs/_posts/ahmedlone127/2024-09-08-argureviews_specificity_roberta_v1_en.md
new file mode 100644
index 00000000000000..bc0dbb5eec5327
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-argureviews_specificity_roberta_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English argureviews_specificity_roberta_v1 XlmRoBertaForSequenceClassification from nihiluis
+author: John Snow Labs
+name: argureviews_specificity_roberta_v1
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`argureviews_specificity_roberta_v1` is a English model originally trained by nihiluis.
+
+{:.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/argureviews_specificity_roberta_v1_en_5.5.0_3.0_1725781294224.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/argureviews_specificity_roberta_v1_en_5.5.0_3.0_1725781294224.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("argureviews_specificity_roberta_v1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("argureviews_specificity_roberta_v1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|argureviews_specificity_roberta_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|834.3 MB|
+
+## References
+
+https://huggingface.co/nihiluis/argureviews-specificity-roberta_v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-atte_1_en.md b/docs/_posts/ahmedlone127/2024-09-08-atte_1_en.md
new file mode 100644
index 00000000000000..8967f8572ddfad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-atte_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English atte_1 RoBertaForSequenceClassification from BaronSch
+author: John Snow Labs
+name: atte_1
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`atte_1` is a English model originally trained by BaronSch.
+
+{:.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/atte_1_en_5.5.0_3.0_1725830447562.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/atte_1_en_5.5.0_3.0_1725830447562.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("atte_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("atte_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|atte_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|468.5 MB|
+
+## References
+
+https://huggingface.co/BaronSch/Atte_1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-atte_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-atte_1_pipeline_en.md
new file mode 100644
index 00000000000000..fcaf3466dd723c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-atte_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English atte_1_pipeline pipeline RoBertaForSequenceClassification from BaronSch
+author: John Snow Labs
+name: atte_1_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`atte_1_pipeline` is a English model originally trained by BaronSch.
+
+{:.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/atte_1_pipeline_en_5.5.0_3.0_1725830470921.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/atte_1_pipeline_en_5.5.0_3.0_1725830470921.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
+
+pipeline = PretrainedPipeline("atte_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("atte_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|atte_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.5 MB|
+
+## References
+
+https://huggingface.co/BaronSch/Atte_1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-atte_2_en.md b/docs/_posts/ahmedlone127/2024-09-08-atte_2_en.md
new file mode 100644
index 00000000000000..9f41fec0299140
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-atte_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English atte_2 RoBertaForSequenceClassification from BaronSch
+author: John Snow Labs
+name: atte_2
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`atte_2` is a English model originally trained by BaronSch.
+
+{:.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/atte_2_en_5.5.0_3.0_1725778584180.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/atte_2_en_5.5.0_3.0_1725778584180.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("atte_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("atte_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|atte_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|468.5 MB|
+
+## References
+
+https://huggingface.co/BaronSch/Atte_2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-auro_0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-auro_0_pipeline_en.md
new file mode 100644
index 00000000000000..d5e9b17e8ae682
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-auro_0_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English auro_0_pipeline pipeline RoBertaForSequenceClassification from BaronSch
+author: John Snow Labs
+name: auro_0_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`auro_0_pipeline` is a English model originally trained by BaronSch.
+
+{:.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/auro_0_pipeline_en_5.5.0_3.0_1725820746631.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/auro_0_pipeline_en_5.5.0_3.0_1725820746631.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
+
+pipeline = PretrainedPipeline("auro_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("auro_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|auro_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.5 MB|
+
+## References
+
+https://huggingface.co/BaronSch/AURO_0
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-autotrain_vfcz5_g4ltr_en.md b/docs/_posts/ahmedlone127/2024-09-08-autotrain_vfcz5_g4ltr_en.md
new file mode 100644
index 00000000000000..2ae687f2ecb8aa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-autotrain_vfcz5_g4ltr_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English autotrain_vfcz5_g4ltr MPNetForSequenceClassification from BloodJackson
+author: John Snow Labs
+name: autotrain_vfcz5_g4ltr
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, mpnet]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_vfcz5_g4ltr` is a English model originally trained by BloodJackson.
+
+{:.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/autotrain_vfcz5_g4ltr_en_5.5.0_3.0_1725826757981.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_vfcz5_g4ltr_en_5.5.0_3.0_1725826757981.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = MPNetForSequenceClassification.pretrained("autotrain_vfcz5_g4ltr","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = MPNetForSequenceClassification.pretrained("autotrain_vfcz5_g4ltr", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|autotrain_vfcz5_g4ltr|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|410.8 MB|
+
+## References
+
+https://huggingface.co/BloodJackson/autotrain-vfcz5-g4ltr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-babyberta_wikipedia_french1_25m_wikipedia1_1_25mm_without_masking_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2024-09-08-babyberta_wikipedia_french1_25m_wikipedia1_1_25mm_without_masking_finetuned_squad_en.md
new file mode 100644
index 00000000000000..4d9e61a433e6c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-babyberta_wikipedia_french1_25m_wikipedia1_1_25mm_without_masking_finetuned_squad_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English babyberta_wikipedia_french1_25m_wikipedia1_1_25mm_without_masking_finetuned_squad RoBertaForQuestionAnswering from lielbin
+author: John Snow Labs
+name: babyberta_wikipedia_french1_25m_wikipedia1_1_25mm_without_masking_finetuned_squad
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`babyberta_wikipedia_french1_25m_wikipedia1_1_25mm_without_masking_finetuned_squad` is a English model originally trained by lielbin.
+
+{:.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/babyberta_wikipedia_french1_25m_wikipedia1_1_25mm_without_masking_finetuned_squad_en_5.5.0_3.0_1725833630687.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/babyberta_wikipedia_french1_25m_wikipedia1_1_25mm_without_masking_finetuned_squad_en_5.5.0_3.0_1725833630687.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("babyberta_wikipedia_french1_25m_wikipedia1_1_25mm_without_masking_finetuned_squad","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("babyberta_wikipedia_french1_25m_wikipedia1_1_25mm_without_masking_finetuned_squad", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|babyberta_wikipedia_french1_25m_wikipedia1_1_25mm_without_masking_finetuned_squad|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|31.9 MB|
+
+## References
+
+https://huggingface.co/lielbin/BabyBERTa-wikipedia_french1.25M_wikipedia1_1.25MM-without-Masking-finetuned-SQuAD
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bda594_fake_news_classification_en.md b/docs/_posts/ahmedlone127/2024-09-08-bda594_fake_news_classification_en.md
new file mode 100644
index 00000000000000..69a33489d4dabf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bda594_fake_news_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bda594_fake_news_classification XlmRoBertaForSequenceClassification from Kaludi
+author: John Snow Labs
+name: bda594_fake_news_classification
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bda594_fake_news_classification` is a English model originally trained by Kaludi.
+
+{:.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/bda594_fake_news_classification_en_5.5.0_3.0_1725799179115.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bda594_fake_news_classification_en_5.5.0_3.0_1725799179115.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("bda594_fake_news_classification","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("bda594_fake_news_classification", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bda594_fake_news_classification|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|791.1 MB|
+
+## References
+
+https://huggingface.co/Kaludi/BDA594-fake-news-classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bda594_fake_news_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-bda594_fake_news_classification_pipeline_en.md
new file mode 100644
index 00000000000000..53a4a2695538c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bda594_fake_news_classification_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bda594_fake_news_classification_pipeline pipeline XlmRoBertaForSequenceClassification from Kaludi
+author: John Snow Labs
+name: bda594_fake_news_classification_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bda594_fake_news_classification_pipeline` is a English model originally trained by Kaludi.
+
+{:.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/bda594_fake_news_classification_pipeline_en_5.5.0_3.0_1725799316454.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bda594_fake_news_classification_pipeline_en_5.5.0_3.0_1725799316454.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
+
+pipeline = PretrainedPipeline("bda594_fake_news_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bda594_fake_news_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bda594_fake_news_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|791.2 MB|
+
+## References
+
+https://huggingface.co/Kaludi/BDA594-fake-news-classification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-beep_kanuri_medium_hate_en.md b/docs/_posts/ahmedlone127/2024-09-08-beep_kanuri_medium_hate_en.md
new file mode 100644
index 00000000000000..554bd6cd92bf60
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-beep_kanuri_medium_hate_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English beep_kanuri_medium_hate BertForSequenceClassification from beomi
+author: John Snow Labs
+name: beep_kanuri_medium_hate
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`beep_kanuri_medium_hate` is a English model originally trained by beomi.
+
+{:.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/beep_kanuri_medium_hate_en_5.5.0_3.0_1725819610603.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/beep_kanuri_medium_hate_en_5.5.0_3.0_1725819610603.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("beep_kanuri_medium_hate","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("beep_kanuri_medium_hate", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|beep_kanuri_medium_hate|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|380.3 MB|
+
+## References
+
+https://huggingface.co/beomi/beep-KR-Medium-hate
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_base_cased_en.md b/docs/_posts/ahmedlone127/2024-09-08-bert_base_cased_en.md
new file mode 100644
index 00000000000000..93c16c4e976961
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_base_cased_en.md
@@ -0,0 +1,104 @@
+---
+layout: model
+title: BERT Embeddings (Base Cased)
+author: John Snow Labs
+name: bert_base_cased
+date: 2024-09-08
+tags: [open_source, embeddings, en, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+This model contains a deep bidirectional transformer trained on Wikipedia and the BookCorpus. The details are described in the paper "[BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://arxiv.org/abs/1810.04805)".
+
+## 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/bert_base_cased_en_5.5.0_3.0_1725837688461.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_en_5.5.0_3.0_1725837688461.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
+...
+embeddings = BertEmbeddings.pretrained("bert_base_cased", "en") \
+.setInputCols("sentence", "token") \
+.setOutputCol("embeddings")
+nlp_pipeline = Pipeline(stages=[document_assembler, sentence_detector, tokenizer, embeddings])
+pipeline_model = nlp_pipeline.fit(spark.createDataFrame([[""]]).toDF("text"))
+result = pipeline_model.transform(spark.createDataFrame([['I love NLP']], ["text"]))
+```
+```scala
+...
+val embeddings = BertEmbeddings.pretrained("bert_base_cased", "en")
+.setInputCols("sentence", "token")
+.setOutputCol("embeddings")
+val pipeline = new Pipeline().setStages(Array(document_assembler, sentence_detector, tokenizer, embeddings))
+val data = Seq("I love NLP").toDF("text")
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+
+text = ["I love NLP"]
+embeddings_df = nlu.load('en.embed.bert.base_cased').predict(text, output_level='token')
+embeddings_df
+```
+</div>
+
+## Results
+
+```bash
+
+Results
+
+	token	en_embed_bert_base_cased_embeddings
+
+	I	[0.43879568576812744, -0.40160006284713745, 0....
+	love	[0.21737590432167053, -0.3865768313407898, -0....
+	NLP	[-0.16226479411125183, -0.053727392107248306, ...
+
+
+
+{:.model-param}
+```
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_cased|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+References
+
+The model is imported from [https://tfhub.dev/google/bert_cased_L-12_H-768_A-12/1](https://tfhub.dev/google/bert_cased_L-12_H-768_A-12/1)
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_base_ner_bulgarian_bg.md b/docs/_posts/ahmedlone127/2024-09-08-bert_base_ner_bulgarian_bg.md
new file mode 100644
index 00000000000000..3e45c51d312768
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_base_ner_bulgarian_bg.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Bulgarian bert_base_ner_bulgarian BertForTokenClassification from auhide
+author: John Snow Labs
+name: bert_base_ner_bulgarian
+date: 2024-09-08
+tags: [bg, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: bg
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_ner_bulgarian` is a Bulgarian model originally trained by auhide.
+
+{:.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/bert_base_ner_bulgarian_bg_5.5.0_3.0_1725822238287.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_ner_bulgarian_bg_5.5.0_3.0_1725822238287.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_base_ner_bulgarian","bg") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_base_ner_bulgarian", "bg")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_ner_bulgarian|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|bg|
+|Size:|665.0 MB|
+
+## References
+
+https://huggingface.co/auhide/bert-base-ner-bulgarian
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_base_ner_bulgarian_pipeline_bg.md b/docs/_posts/ahmedlone127/2024-09-08-bert_base_ner_bulgarian_pipeline_bg.md
new file mode 100644
index 00000000000000..95f9d59a9074b9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_base_ner_bulgarian_pipeline_bg.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Bulgarian bert_base_ner_bulgarian_pipeline pipeline BertForTokenClassification from auhide
+author: John Snow Labs
+name: bert_base_ner_bulgarian_pipeline
+date: 2024-09-08
+tags: [bg, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: bg
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_ner_bulgarian_pipeline` is a Bulgarian model originally trained by auhide.
+
+{:.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/bert_base_ner_bulgarian_pipeline_bg_5.5.0_3.0_1725822271026.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_ner_bulgarian_pipeline_bg_5.5.0_3.0_1725822271026.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
+
+pipeline = PretrainedPipeline("bert_base_ner_bulgarian_pipeline", lang = "bg")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_ner_bulgarian_pipeline", lang = "bg")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_ner_bulgarian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|bg|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/auhide/bert-base-ner-bulgarian
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_base_uncased_abusive_oriya_threatening_speech_en.md b/docs/_posts/ahmedlone127/2024-09-08-bert_base_uncased_abusive_oriya_threatening_speech_en.md
new file mode 100644
index 00000000000000..94467214a9ed41
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_base_uncased_abusive_oriya_threatening_speech_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_abusive_oriya_threatening_speech BertForSequenceClassification from DunnBC22
+author: John Snow Labs
+name: bert_base_uncased_abusive_oriya_threatening_speech
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_abusive_oriya_threatening_speech` is a English model originally trained by DunnBC22.
+
+{:.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/bert_base_uncased_abusive_oriya_threatening_speech_en_5.5.0_3.0_1725802041250.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_abusive_oriya_threatening_speech_en_5.5.0_3.0_1725802041250.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bert_base_uncased_abusive_oriya_threatening_speech","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_abusive_oriya_threatening_speech", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_abusive_oriya_threatening_speech|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/DunnBC22/bert-base-uncased-Abusive_Or_Threatening_Speech
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_base_uncased_finetuned_mrpc_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-bert_base_uncased_finetuned_mrpc_v2_pipeline_en.md
new file mode 100644
index 00000000000000..1078704564c347
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_base_uncased_finetuned_mrpc_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_finetuned_mrpc_v2_pipeline pipeline BertForSequenceClassification from sadhaklal
+author: John Snow Labs
+name: bert_base_uncased_finetuned_mrpc_v2_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_mrpc_v2_pipeline` is a English model originally trained by sadhaklal.
+
+{:.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/bert_base_uncased_finetuned_mrpc_v2_pipeline_en_5.5.0_3.0_1725838835044.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mrpc_v2_pipeline_en_5.5.0_3.0_1725838835044.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
+
+pipeline = PretrainedPipeline("bert_base_uncased_finetuned_mrpc_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_mrpc_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_finetuned_mrpc_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/sadhaklal/bert-base-uncased-finetuned-mrpc-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_base_uncased_mnli_from_bert_large_uncased_mnli_en.md b/docs/_posts/ahmedlone127/2024-09-08-bert_base_uncased_mnli_from_bert_large_uncased_mnli_en.md
new file mode 100644
index 00000000000000..bdbf3b98390132
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_base_uncased_mnli_from_bert_large_uncased_mnli_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_uncased_mnli_from_bert_large_uncased_mnli BertForSequenceClassification from yoshitomo-matsubara
+author: John Snow Labs
+name: bert_base_uncased_mnli_from_bert_large_uncased_mnli
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_mnli_from_bert_large_uncased_mnli` is a English model originally trained by yoshitomo-matsubara.
+
+{:.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/bert_base_uncased_mnli_from_bert_large_uncased_mnli_en_5.5.0_3.0_1725839187039.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_mnli_from_bert_large_uncased_mnli_en_5.5.0_3.0_1725839187039.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bert_base_uncased_mnli_from_bert_large_uncased_mnli","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_mnli_from_bert_large_uncased_mnli", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_mnli_from_bert_large_uncased_mnli|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/yoshitomo-matsubara/bert-base-uncased-mnli_from_bert-large-uncased-mnli
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_base_uncased_mnli_from_bert_large_uncased_mnli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-bert_base_uncased_mnli_from_bert_large_uncased_mnli_pipeline_en.md
new file mode 100644
index 00000000000000..a3930324191111
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_base_uncased_mnli_from_bert_large_uncased_mnli_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_base_uncased_mnli_from_bert_large_uncased_mnli_pipeline pipeline BertForSequenceClassification from yoshitomo-matsubara
+author: John Snow Labs
+name: bert_base_uncased_mnli_from_bert_large_uncased_mnli_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_mnli_from_bert_large_uncased_mnli_pipeline` is a English model originally trained by yoshitomo-matsubara.
+
+{:.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/bert_base_uncased_mnli_from_bert_large_uncased_mnli_pipeline_en_5.5.0_3.0_1725839207715.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_mnli_from_bert_large_uncased_mnli_pipeline_en_5.5.0_3.0_1725839207715.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
+
+pipeline = PretrainedPipeline("bert_base_uncased_mnli_from_bert_large_uncased_mnli_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_base_uncased_mnli_from_bert_large_uncased_mnli_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_uncased_mnli_from_bert_large_uncased_mnli_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/yoshitomo-matsubara/bert-base-uncased-mnli_from_bert-large-uncased-mnli
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_base_yelp_reviews_en.md b/docs/_posts/ahmedlone127/2024-09-08-bert_base_yelp_reviews_en.md
new file mode 100644
index 00000000000000..3248e5535b32b9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_base_yelp_reviews_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_base_yelp_reviews BertForSequenceClassification from saitejautpala
+author: John Snow Labs
+name: bert_base_yelp_reviews
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_yelp_reviews` is a English model originally trained by saitejautpala.
+
+{:.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/bert_base_yelp_reviews_en_5.5.0_3.0_1725767856503.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_yelp_reviews_en_5.5.0_3.0_1725767856503.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bert_base_yelp_reviews","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_yelp_reviews", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_yelp_reviews|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|405.9 MB|
+
+## References
+
+https://huggingface.co/saitejautpala/bert-base-yelp-reviews
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_bregman_es.md b/docs/_posts/ahmedlone127/2024-09-08-bert_bregman_es.md
new file mode 100644
index 00000000000000..a8ec6c18504ac3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_bregman_es.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Castilian, Spanish bert_bregman XlmRoBertaForSequenceClassification from nmarinnn
+author: John Snow Labs
+name: bert_bregman
+date: 2024-09-08
+tags: [es, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_bregman` is a Castilian, Spanish model originally trained by nmarinnn.
+
+{:.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/bert_bregman_es_5.5.0_3.0_1725799129273.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_bregman_es_5.5.0_3.0_1725799129273.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("bert_bregman","es") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("bert_bregman", "es")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_bregman|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|es|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/nmarinnn/bert-bregman
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_bregman_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-08-bert_bregman_pipeline_es.md
new file mode 100644
index 00000000000000..273cc48bcfaa95
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_bregman_pipeline_es.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Castilian, Spanish bert_bregman_pipeline pipeline XlmRoBertaForSequenceClassification from nmarinnn
+author: John Snow Labs
+name: bert_bregman_pipeline
+date: 2024-09-08
+tags: [es, open_source, pipeline, onnx]
+task: Text Classification
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_bregman_pipeline` is a Castilian, Spanish model originally trained by nmarinnn.
+
+{:.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/bert_bregman_pipeline_es_5.5.0_3.0_1725799180296.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_bregman_pipeline_es_5.5.0_3.0_1725799180296.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
+
+pipeline = PretrainedPipeline("bert_bregman_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_bregman_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_bregman_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/nmarinnn/bert-bregman
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_classifier_autotrain_j_multi_classification_1181044057_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-08-bert_classifier_autotrain_j_multi_classification_1181044057_pipeline_ar.md
new file mode 100644
index 00000000000000..e40e614433c947
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_classifier_autotrain_j_multi_classification_1181044057_pipeline_ar.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Arabic bert_classifier_autotrain_j_multi_classification_1181044057_pipeline pipeline BertForSequenceClassification from azizkh
+author: John Snow Labs
+name: bert_classifier_autotrain_j_multi_classification_1181044057_pipeline
+date: 2024-09-08
+tags: [ar, open_source, pipeline, onnx]
+task: Text Classification
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_autotrain_j_multi_classification_1181044057_pipeline` is a Arabic model originally trained by azizkh.
+
+{:.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/bert_classifier_autotrain_j_multi_classification_1181044057_pipeline_ar_5.5.0_3.0_1725801841252.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_autotrain_j_multi_classification_1181044057_pipeline_ar_5.5.0_3.0_1725801841252.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
+
+pipeline = PretrainedPipeline("bert_classifier_autotrain_j_multi_classification_1181044057_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_classifier_autotrain_j_multi_classification_1181044057_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_classifier_autotrain_j_multi_classification_1181044057_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|507.3 MB|
+
+## References
+
+https://huggingface.co/azizkh/autotrain-j-multi-classification-1181044057
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_classifier_autotrain_not_interested_2_1213045881_en.md b/docs/_posts/ahmedlone127/2024-09-08-bert_classifier_autotrain_not_interested_2_1213045881_en.md
new file mode 100644
index 00000000000000..cbda2985ae212d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_classifier_autotrain_not_interested_2_1213045881_en.md
@@ -0,0 +1,104 @@
+---
+layout: model
+title: English BertForSequenceClassification Cased model (from aujer)
+author: John Snow Labs
+name: bert_classifier_autotrain_not_interested_2_1213045881
+date: 2024-09-08
+tags: [en, open_source, bert, sequence_classification, classification, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `autotrain-not_interested_2-1213045881` is a English model originally trained by `aujer`.
+
+## Predicted Entities
+
+`ROLE_FIT`, `COMPANY_FIT`, `TIMING`, `SENIORITY`, `REMOTE_POLICY`, `COMPENSATION`, `VISA`, `OTHER`
+
+{:.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/bert_classifier_autotrain_not_interested_2_1213045881_en_5.5.0_3.0_1725802383120.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_autotrain_not_interested_2_1213045881_en_5.5.0_3.0_1725802383120.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
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_autotrain_not_interested_2_1213045881","en") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("class")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+      .setInputCols(Array("text"))
+      .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_autotrain_not_interested_2_1213045881","en")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("class")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.classify.not_interested..bert.by_aujer").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_classifier_autotrain_not_interested_2_1213045881|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+References
+
+- https://huggingface.co/aujer/autotrain-not_interested_2-1213045881
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_classifier_sead_l_6_h_256_a_8_qnli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-bert_classifier_sead_l_6_h_256_a_8_qnli_pipeline_en.md
new file mode 100644
index 00000000000000..9aeedd94d7c521
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_classifier_sead_l_6_h_256_a_8_qnli_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_classifier_sead_l_6_h_256_a_8_qnli_pipeline pipeline BertForSequenceClassification from course5i
+author: John Snow Labs
+name: bert_classifier_sead_l_6_h_256_a_8_qnli_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_sead_l_6_h_256_a_8_qnli_pipeline` is a English model originally trained by course5i.
+
+{:.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/bert_classifier_sead_l_6_h_256_a_8_qnli_pipeline_en_5.5.0_3.0_1725761423111.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_sead_l_6_h_256_a_8_qnli_pipeline_en_5.5.0_3.0_1725761423111.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
+
+pipeline = PretrainedPipeline("bert_classifier_sead_l_6_h_256_a_8_qnli_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_classifier_sead_l_6_h_256_a_8_qnli_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_classifier_sead_l_6_h_256_a_8_qnli_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|47.4 MB|
+
+## References
+
+https://huggingface.co/course5i/SEAD-L-6_H-256_A-8-qnli
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_classifier_sead_l_6_h_256_a_8_sst2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-bert_classifier_sead_l_6_h_256_a_8_sst2_pipeline_en.md
new file mode 100644
index 00000000000000..9ce6f3f1181f5a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_classifier_sead_l_6_h_256_a_8_sst2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_classifier_sead_l_6_h_256_a_8_sst2_pipeline pipeline BertForSequenceClassification from course5i
+author: John Snow Labs
+name: bert_classifier_sead_l_6_h_256_a_8_sst2_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_sead_l_6_h_256_a_8_sst2_pipeline` is a English model originally trained by course5i.
+
+{:.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/bert_classifier_sead_l_6_h_256_a_8_sst2_pipeline_en_5.5.0_3.0_1725801665800.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_sead_l_6_h_256_a_8_sst2_pipeline_en_5.5.0_3.0_1725801665800.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
+
+pipeline = PretrainedPipeline("bert_classifier_sead_l_6_h_256_a_8_sst2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_classifier_sead_l_6_h_256_a_8_sst2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_classifier_sead_l_6_h_256_a_8_sst2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|47.3 MB|
+
+## References
+
+https://huggingface.co/course5i/SEAD-L-6_H-256_A-8-sst2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_classifier_taipeiqa_v1_en.md b/docs/_posts/ahmedlone127/2024-09-08-bert_classifier_taipeiqa_v1_en.md
new file mode 100644
index 00000000000000..34344cedac872b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_classifier_taipeiqa_v1_en.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: English BertForSequenceClassification Cased model (from nicktien)
+author: John Snow Labs
+name: bert_classifier_taipeiqa_v1
+date: 2024-09-08
+tags: [bert, sequence_classification, classification, open_source, en, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `TaipeiQA_v1` is a English model originally trained by `nicktien`.
+
+## Predicted Entities
+
+`臺北市就業服務處`, `臺北市停車管理工程處`, `臺北市政府教育局終身教育科`, `臺北市政府教育局國小教育科`, `臺北市政府衛生局醫事管理科`, `臺北市商業處`, `臺北市政府地政局土地開發科`, `臺北市信義區公所`, `臺北市立天文科學教育館`, `臺北市市場處公有零售市場科`, `臺北市政府地政局地權及不動產交易科`, `臺北市藝文推廣處`, `臺北市政府環境保護局北投垃圾焚化廠`, `臺北市政府產業發展局科技產業服務中心`, `臺北市政府警察局刑事警察大隊`, `臺北市政府資訊局應用服務組`, `臺北市動物保護處動物救援隊`, `臺北市交通事件裁決所違規申訴課`, `臺北市中山堂管理所`, `臺北市立文獻館`, `臺北市勞動檢查處`, `臺北市政府勞動局`, `臺北市政府資訊局綜合企劃組`, `臺北市政府都市發展局`, `臺北市立聯合醫院昆明防治中心`, `臺北市立美術館`, `臺北市青少年發展處`, `臺北市政府環境保護局環保稽查大隊`, `臺北市立聯合醫院`, `臺北市政府環境保護局環境清潔管理科`, `臺北市政府捷運工程局南區工程處`, `臺北市政府交通局交通治理科`, `臺北市政府工務局新建工程處工程配合科`, `臺北市政府客家事務委員會`, `臺北市政府工務局大地工程處`, `臺北市建築管理工程處使用科`, `臺北市內湖區公所`, `臺北市市政大樓公共事務管理中心`, `臺北市政府社會局`, `臺北市公共運輸處大眾運輸科`, `臺北市交通管制工程處設施科`, `臺北市政府人事處考訓科`, `臺北市都市更新處`, `臺北市交通事件裁決所案件管理課`, `臺北市政府交通局`, `臺北自來水事業處`, `臺北市政府環境保護局秘書室`, `臺北市公共運輸處業務稽查科`, `臺北市建築管理工程處公寓大廈科`, `臺北市稅捐稽徵處稅務管理科`, `臺北市政府勞動局職業安全衛生科`, `臺北市動物保護處產業保育組`, `臺北市政府教育局綜合企劃科`, `臺北市政府工務局衛生下水道工程處營運管理科`, `臺北市政府民政局戶籍行政科`, `臺北市政府勞動局勞資關係科`, `臺北市政府捷運工程局機電系統工程處`, `臺北市政府環境保護局廢棄物處理場`, `臺北市政府研究發展考核委員會`, `臺北市稅捐稽徵處法務科`, `臺北市政府工務局公園路燈工程管理處青年公園管理所`, `臺北市動物保護處防疫檢驗組`, `臺北市政府教育局特殊教育科`, `臺北市政府衛生局長期照護科`, `臺北翡翠水庫管理局`, `臺北市政府衛生局食品藥物管理科`, `臺北市政府民政局區政監督科`, `臺北市政府教育局中等教育科`, `臺北市交通事件裁決所違規裁罰課`, `臺北市勞動力重建運用處`, `臺北市建築管理工程處施工科`, `臺北市動物保護處動物管理組`, `臺北市政府社會局婦女福利及兒童托育科`, `臺北市政府環境保護局木柵垃圾焚化廠`, `臺北市政府消防局`, `臺北市政府衛生局疾病管制科`, `臺北市政府主計處`, `臺北市政府產業發展局工商服務科`, `臺北市政府社會局社會工作科`, `臺北市政府社會局兒童及少年福利科`, `臺北市立陽明教養院`, `臺北市政府人事處給與科`, `臺北市政府體育局`, `臺北市政府工務局`, `臺北市政府警察局交通警察大隊`, `臺北市政府工務局公園路燈工程管理處園藝工程隊`, `臺北市公共運輸處一般運輸科`, `臺北市政府原住民族事務委員會`, `臺北市政府環境保護局內湖垃圾焚化廠`, `臺北市政府勞動局勞動教育文化科`, `臺北市建築管理工程處建照科`, `臺北市立圖書館`, `臺北市政府地政局測繪科`, `臺北市政府警察局`, `臺北市稅捐稽徵處企劃服務科`, `臺北市動產質借處業務組`, `臺北市政府工務局新建工程處共同管道科`, `臺北市政府文化局藝術發展科`, `臺北市政府財政局菸酒暨稅務管理科`, `臺北市政府環境保護局資源循環管理科`, `臺北市政府工務局衛生下水道工程處迪化污水處理廠`, `臺北市政府警察局婦幼警察隊`, `臺北市職能發展學院`, `臺北市政府衛生局健康管理科`, `臺北市政府教育局人事室`, `臺北市政府教育局體育及衛生保健科`, `臺北市政府工務局公園路燈工程管理處`, `臺北市政府工務局水利工程處河川管理科`, `臺北市政府民政局人口政策科`, `臺北市政府社會局老人福利科`, `臺北市公共運輸處綜合規劃科`, `臺北市政府觀光傳播局`, `臺北市政府勞動局勞動基準科`, `臺北市政府都市發展局都市測量科`, `臺北市政府教育局學前教育科`, `臺北市稅捐稽徵處機會稅科`, `臺北市政府環境保護局廢棄物處理管理科`, `臺北市政府文化局`, `臺北市政府兵役局`, `臺北市政府環境保護局綜合企劃科`, `臺北市政府捷運工程局`, `臺北市政府社會局人民團體科`, `臺北市政府民政局宗教禮俗科`, `臺北市政府環境保護局空污噪音防制科`, `臺北市政府地政局地用科`, `臺北市動物保護處動物收容組`, `臺北市立動物園`, `臺北市政府環境保護局水質病媒管制科`, `臺北市政府法務局`, `臺北市政府資訊局設備網路組`, `臺北市政府教育局軍訓室`, `臺北大眾捷運股份有限公司`, `臺北市政府地政局地價科`, `臺北市政府社會局身心障礙者福利科`, `臺北市市場處批發市場科`, `臺北市稅捐稽徵處財產稅科`, `臺北市政府工務局衛生下水道工程處`, `臺北市政府勞動局就業安全科`, `臺北市市場處攤販科`, `臺北市政府地政局土地登記科`, `臺北市政府秘書處`, `臺北市政府教育局資訊教育科`, `臺北市政府社會局社會救助科`, `臺北市政府公務人員訓練處`, `臺北市政府產業發展局公用事業科`, `臺北市政府產業發展局農業發展科`, `臺北市交通事件裁決所肇事鑑定課`, `臺北市殯葬管理處`, `臺北市政府工務局水利工程處雨水下水道工程科`
+
+{:.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/bert_classifier_taipeiqa_v1_en_5.5.0_3.0_1725801522689.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_taipeiqa_v1_en_5.5.0_3.0_1725801522689.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
+documentAssembler = DocumentAssembler() \
+        .setInputCol("text") \
+        .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_taipeiqa_v1","en") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("class")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer,sequenceClassifier_loaded])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+          .setInputCol("text") 
+          .setOutputCol("document")
+
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_taipeiqa_v1","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("class")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer,sequenceClassifier_loaded))
+
+val data = Seq("PUT YOUR STRING HERE").toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_classifier_taipeiqa_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|383.7 MB|
+
+## References
+
+References
+
+- https://huggingface.co/nicktien/TaipeiQA_v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_classifier_taipeiqa_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-bert_classifier_taipeiqa_v1_pipeline_en.md
new file mode 100644
index 00000000000000..3f616e92130348
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_classifier_taipeiqa_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_classifier_taipeiqa_v1_pipeline pipeline BertForSequenceClassification from nicktien
+author: John Snow Labs
+name: bert_classifier_taipeiqa_v1_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_taipeiqa_v1_pipeline` is a English model originally trained by nicktien.
+
+{:.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/bert_classifier_taipeiqa_v1_pipeline_en_5.5.0_3.0_1725801540727.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_taipeiqa_v1_pipeline_en_5.5.0_3.0_1725801540727.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
+
+pipeline = PretrainedPipeline("bert_classifier_taipeiqa_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_classifier_taipeiqa_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_classifier_taipeiqa_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|383.7 MB|
+
+## References
+
+https://huggingface.co/nicktien/TaipeiQA_v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_embeddings_bert_for_patents_en.md b/docs/_posts/ahmedlone127/2024-09-08-bert_embeddings_bert_for_patents_en.md
new file mode 100644
index 00000000000000..b445e726124309
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_embeddings_bert_for_patents_en.md
@@ -0,0 +1,110 @@
+---
+layout: model
+title: English Bert Embeddings (from anferico)
+author: John Snow Labs
+name: bert_embeddings_bert_for_patents
+date: 2024-09-08
+tags: [bert, embeddings, en, open_source, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Bert Embeddings model, uploaded to Hugging Face, adapted and imported into Spark NLP. `bert-for-patents` is a English model orginally trained by `anferico`.
+
+## 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/bert_embeddings_bert_for_patents_en_5.5.0_3.0_1725793051189.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_embeddings_bert_for_patents_en_5.5.0_3.0_1725793051189.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
+documentAssembler = DocumentAssembler() \
+.setInputCol("text") \
+.setOutputCol("document")
+
+tokenizer = Tokenizer() \
+.setInputCols("document") \
+.setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_embeddings_bert_for_patents","en") \
+.setInputCols(["document", "token"]) \
+.setOutputCol("embeddings")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings])
+
+data = spark.createDataFrame([["I love Spark NLP"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+.setInputCol("text") 
+.setOutputCol("document")
+
+val tokenizer = new Tokenizer() 
+.setInputCols(Array("document"))
+.setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_embeddings_bert_for_patents","en") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+
+val data = Seq("I love Spark NLP").toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.embed.bert_for_patents").predict("""I love Spark NLP""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_embeddings_bert_for_patents|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+References
+
+- https://huggingface.co/anferico/bert-for-patents
+- https://cloud.google.com/blog/products/ai-machine-learning/how-ai-improves-patent-analysis
+- https://services.google.com/fh/files/blogs/bert_for_patents_white_paper.pdf
+- https://github.com/google/patents-public-data/blob/master/models/BERT%20for%20Patents.md
+- https://github.com/ec-jrc/Patents4IPPC
+- https://picampus-school.com/
+- https://ec.europa.eu/jrc/en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_embeddings_bert_for_patents_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-bert_embeddings_bert_for_patents_pipeline_en.md
new file mode 100644
index 00000000000000..66786002e9b702
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_embeddings_bert_for_patents_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_embeddings_bert_for_patents_pipeline pipeline BertEmbeddings from anferico
+author: John Snow Labs
+name: bert_embeddings_bert_for_patents_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_embeddings_bert_for_patents_pipeline` is a English model originally trained by anferico.
+
+{:.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/bert_embeddings_bert_for_patents_pipeline_en_5.5.0_3.0_1725793109032.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_embeddings_bert_for_patents_pipeline_en_5.5.0_3.0_1725793109032.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
+
+pipeline = PretrainedPipeline("bert_embeddings_bert_for_patents_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_embeddings_bert_for_patents_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_embeddings_bert_for_patents_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/anferico/bert-for-patents
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_finetuned_ner4_csariyildiz_en.md b/docs/_posts/ahmedlone127/2024-09-08-bert_finetuned_ner4_csariyildiz_en.md
new file mode 100644
index 00000000000000..01a09db60c6019
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_finetuned_ner4_csariyildiz_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner4_csariyildiz BertForTokenClassification from csariyildiz
+author: John Snow Labs
+name: bert_finetuned_ner4_csariyildiz
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner4_csariyildiz` is a English model originally trained by csariyildiz.
+
+{:.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/bert_finetuned_ner4_csariyildiz_en_5.5.0_3.0_1725835212490.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner4_csariyildiz_en_5.5.0_3.0_1725835212490.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_finetuned_ner4_csariyildiz","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner4_csariyildiz", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner4_csariyildiz|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/csariyildiz/bert-finetuned-ner4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_finetuned_ner_t1_en.md b/docs/_posts/ahmedlone127/2024-09-08-bert_finetuned_ner_t1_en.md
new file mode 100644
index 00000000000000..2d42b1212702a4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_finetuned_ner_t1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_ner_t1 DistilBertForTokenClassification from avi10
+author: John Snow Labs
+name: bert_finetuned_ner_t1
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_t1` is a English model originally trained by avi10.
+
+{:.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/bert_finetuned_ner_t1_en_5.5.0_3.0_1725837279528.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_t1_en_5.5.0_3.0_1725837279528.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("bert_finetuned_ner_t1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("bert_finetuned_ner_t1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_ner_t1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/avi10/bert-finetuned-ner-T1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_finetuned_sentiment_classification_yelp_en.md b/docs/_posts/ahmedlone127/2024-09-08-bert_finetuned_sentiment_classification_yelp_en.md
new file mode 100644
index 00000000000000..8dfb95f5adc41b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_finetuned_sentiment_classification_yelp_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_finetuned_sentiment_classification_yelp BertForSequenceClassification from karimbkh
+author: John Snow Labs
+name: bert_finetuned_sentiment_classification_yelp
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_sentiment_classification_yelp` is a English model originally trained by karimbkh.
+
+{:.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/bert_finetuned_sentiment_classification_yelp_en_5.5.0_3.0_1725819315043.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_sentiment_classification_yelp_en_5.5.0_3.0_1725819315043.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bert_finetuned_sentiment_classification_yelp","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_sentiment_classification_yelp", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_sentiment_classification_yelp|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/karimbkh/BERT_fineTuned_Sentiment_Classification_Yelp
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_finetuned_sentiment_classification_yelp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-bert_finetuned_sentiment_classification_yelp_pipeline_en.md
new file mode 100644
index 00000000000000..c4b06f18c6d67b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_finetuned_sentiment_classification_yelp_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_finetuned_sentiment_classification_yelp_pipeline pipeline BertForSequenceClassification from karimbkh
+author: John Snow Labs
+name: bert_finetuned_sentiment_classification_yelp_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_sentiment_classification_yelp_pipeline` is a English model originally trained by karimbkh.
+
+{:.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/bert_finetuned_sentiment_classification_yelp_pipeline_en_5.5.0_3.0_1725819341207.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_sentiment_classification_yelp_pipeline_en_5.5.0_3.0_1725819341207.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
+
+pipeline = PretrainedPipeline("bert_finetuned_sentiment_classification_yelp_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_finetuned_sentiment_classification_yelp_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_finetuned_sentiment_classification_yelp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/karimbkh/BERT_fineTuned_Sentiment_Classification_Yelp
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_french_ner_datascience_service_en.md b/docs/_posts/ahmedlone127/2024-09-08-bert_french_ner_datascience_service_en.md
new file mode 100644
index 00000000000000..aca994b0fc896c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_french_ner_datascience_service_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_french_ner_datascience_service BertForTokenClassification from datascience-service
+author: John Snow Labs
+name: bert_french_ner_datascience_service
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_french_ner_datascience_service` is a English model originally trained by datascience-service.
+
+{:.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/bert_french_ner_datascience_service_en_5.5.0_3.0_1725834889373.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_french_ner_datascience_service_en_5.5.0_3.0_1725834889373.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_french_ner_datascience_service","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_french_ner_datascience_service", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_french_ner_datascience_service|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/datascience-service/bert-french-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_imdb_lvwerra_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-bert_imdb_lvwerra_pipeline_en.md
new file mode 100644
index 00000000000000..788a25581d5bf5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_imdb_lvwerra_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_imdb_lvwerra_pipeline pipeline BertForSequenceClassification from lvwerra
+author: John Snow Labs
+name: bert_imdb_lvwerra_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_imdb_lvwerra_pipeline` is a English model originally trained by lvwerra.
+
+{:.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/bert_imdb_lvwerra_pipeline_en_5.5.0_3.0_1725826319082.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_imdb_lvwerra_pipeline_en_5.5.0_3.0_1725826319082.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
+
+pipeline = PretrainedPipeline("bert_imdb_lvwerra_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_imdb_lvwerra_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_imdb_lvwerra_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/lvwerra/bert-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_large_uncased_mrpc_en.md b/docs/_posts/ahmedlone127/2024-09-08-bert_large_uncased_mrpc_en.md
new file mode 100644
index 00000000000000..15c18f1644a590
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_large_uncased_mrpc_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_large_uncased_mrpc BertForSequenceClassification from yoshitomo-matsubara
+author: John Snow Labs
+name: bert_large_uncased_mrpc
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_mrpc` is a English model originally trained by yoshitomo-matsubara.
+
+{:.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/bert_large_uncased_mrpc_en_5.5.0_3.0_1725801918186.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_mrpc_en_5.5.0_3.0_1725801918186.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bert_large_uncased_mrpc","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_mrpc", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_large_uncased_mrpc|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/yoshitomo-matsubara/bert-large-uncased-mrpc
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_lead_norwegian_lead_en.md b/docs/_posts/ahmedlone127/2024-09-08-bert_lead_norwegian_lead_en.md
new file mode 100644
index 00000000000000..afcebdb59d941b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_lead_norwegian_lead_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_lead_norwegian_lead BertForSequenceClassification from Prabhjot410
+author: John Snow Labs
+name: bert_lead_norwegian_lead
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_lead_norwegian_lead` is a English model originally trained by Prabhjot410.
+
+{:.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/bert_lead_norwegian_lead_en_5.5.0_3.0_1725801772395.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_lead_norwegian_lead_en_5.5.0_3.0_1725801772395.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bert_lead_norwegian_lead","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bert_lead_norwegian_lead", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_lead_norwegian_lead|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/Prabhjot410/bert-lead-no-lead
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_lead_norwegian_lead_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-bert_lead_norwegian_lead_pipeline_en.md
new file mode 100644
index 00000000000000..305586179ab4e4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_lead_norwegian_lead_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_lead_norwegian_lead_pipeline pipeline BertForSequenceClassification from Prabhjot410
+author: John Snow Labs
+name: bert_lead_norwegian_lead_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_lead_norwegian_lead_pipeline` is a English model originally trained by Prabhjot410.
+
+{:.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/bert_lead_norwegian_lead_pipeline_en_5.5.0_3.0_1725801793015.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_lead_norwegian_lead_pipeline_en_5.5.0_3.0_1725801793015.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
+
+pipeline = PretrainedPipeline("bert_lead_norwegian_lead_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_lead_norwegian_lead_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_lead_norwegian_lead_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/Prabhjot410/bert-lead-no-lead
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_polish_sentiment_politics_pipeline_pl.md b/docs/_posts/ahmedlone127/2024-09-08-bert_polish_sentiment_politics_pipeline_pl.md
new file mode 100644
index 00000000000000..1b9908fc6aab71
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_polish_sentiment_politics_pipeline_pl.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Polish bert_polish_sentiment_politics_pipeline pipeline BertForSequenceClassification from eevvgg
+author: John Snow Labs
+name: bert_polish_sentiment_politics_pipeline
+date: 2024-09-08
+tags: [pl, open_source, pipeline, onnx]
+task: Text Classification
+language: pl
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_polish_sentiment_politics_pipeline` is a Polish model originally trained by eevvgg.
+
+{:.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/bert_polish_sentiment_politics_pipeline_pl_5.5.0_3.0_1725838948305.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_polish_sentiment_politics_pipeline_pl_5.5.0_3.0_1725838948305.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
+
+pipeline = PretrainedPipeline("bert_polish_sentiment_politics_pipeline", lang = "pl")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_polish_sentiment_politics_pipeline", lang = "pl")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_polish_sentiment_politics_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|pl|
+|Size:|495.8 MB|
+
+## References
+
+https://huggingface.co/eevvgg/bert-polish-sentiment-politics
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_query_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-bert_query_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..8ef4af67583e57
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_query_classifier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_query_classifier_pipeline pipeline BertForSequenceClassification from wanderer2k1
+author: John Snow Labs
+name: bert_query_classifier_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_query_classifier_pipeline` is a English model originally trained by wanderer2k1.
+
+{:.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/bert_query_classifier_pipeline_en_5.5.0_3.0_1725768509771.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_query_classifier_pipeline_en_5.5.0_3.0_1725768509771.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
+
+pipeline = PretrainedPipeline("bert_query_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_query_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_query_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|501.4 MB|
+
+## References
+
+https://huggingface.co/wanderer2k1/BERT-query-classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_sayula_popoluca_bert_base_han_chinese_sayula_popoluca_pipeline_zh.md b/docs/_posts/ahmedlone127/2024-09-08-bert_sayula_popoluca_bert_base_han_chinese_sayula_popoluca_pipeline_zh.md
new file mode 100644
index 00000000000000..052fdaeb557257
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_sayula_popoluca_bert_base_han_chinese_sayula_popoluca_pipeline_zh.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Chinese bert_sayula_popoluca_bert_base_han_chinese_sayula_popoluca_pipeline pipeline BertForTokenClassification from ckiplab
+author: John Snow Labs
+name: bert_sayula_popoluca_bert_base_han_chinese_sayula_popoluca_pipeline
+date: 2024-09-08
+tags: [zh, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: zh
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sayula_popoluca_bert_base_han_chinese_sayula_popoluca_pipeline` is a Chinese model originally trained by ckiplab.
+
+{:.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/bert_sayula_popoluca_bert_base_han_chinese_sayula_popoluca_pipeline_zh_5.5.0_3.0_1725822237494.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sayula_popoluca_bert_base_han_chinese_sayula_popoluca_pipeline_zh_5.5.0_3.0_1725822237494.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
+
+pipeline = PretrainedPipeline("bert_sayula_popoluca_bert_base_han_chinese_sayula_popoluca_pipeline", lang = "zh")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_sayula_popoluca_bert_base_han_chinese_sayula_popoluca_pipeline", lang = "zh")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_sayula_popoluca_bert_base_han_chinese_sayula_popoluca_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|zh|
+|Size:|396.9 MB|
+
+## References
+
+https://huggingface.co/ckiplab/bert-base-han-chinese-pos
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_sayula_popoluca_bert_base_han_chinese_sayula_popoluca_zh.md b/docs/_posts/ahmedlone127/2024-09-08-bert_sayula_popoluca_bert_base_han_chinese_sayula_popoluca_zh.md
new file mode 100644
index 00000000000000..e198459371a1bb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_sayula_popoluca_bert_base_han_chinese_sayula_popoluca_zh.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Chinese bert_sayula_popoluca_bert_base_han_chinese_sayula_popoluca BertForTokenClassification from ckiplab
+author: John Snow Labs
+name: bert_sayula_popoluca_bert_base_han_chinese_sayula_popoluca
+date: 2024-09-08
+tags: [zh, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: zh
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sayula_popoluca_bert_base_han_chinese_sayula_popoluca` is a Chinese model originally trained by ckiplab.
+
+{:.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/bert_sayula_popoluca_bert_base_han_chinese_sayula_popoluca_zh_5.5.0_3.0_1725822218079.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sayula_popoluca_bert_base_han_chinese_sayula_popoluca_zh_5.5.0_3.0_1725822218079.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_sayula_popoluca_bert_base_han_chinese_sayula_popoluca","zh") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_sayula_popoluca_bert_base_han_chinese_sayula_popoluca", "zh")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_sayula_popoluca_bert_base_han_chinese_sayula_popoluca|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|zh|
+|Size:|396.8 MB|
+
+## References
+
+https://huggingface.co/ckiplab/bert-base-han-chinese-pos
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bert_southern_sotho_qa_multi_qa_mpnet_base_dot_v1_game_183_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-bert_southern_sotho_qa_multi_qa_mpnet_base_dot_v1_game_183_pipeline_en.md
new file mode 100644
index 00000000000000..bd3ed57e5fae35
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bert_southern_sotho_qa_multi_qa_mpnet_base_dot_v1_game_183_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bert_southern_sotho_qa_multi_qa_mpnet_base_dot_v1_game_183_pipeline pipeline MPNetEmbeddings from abhijitt
+author: John Snow Labs
+name: bert_southern_sotho_qa_multi_qa_mpnet_base_dot_v1_game_183_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_southern_sotho_qa_multi_qa_mpnet_base_dot_v1_game_183_pipeline` is a English model originally trained by abhijitt.
+
+{:.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/bert_southern_sotho_qa_multi_qa_mpnet_base_dot_v1_game_183_pipeline_en_5.5.0_3.0_1725817527060.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_southern_sotho_qa_multi_qa_mpnet_base_dot_v1_game_183_pipeline_en_5.5.0_3.0_1725817527060.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
+
+pipeline = PretrainedPipeline("bert_southern_sotho_qa_multi_qa_mpnet_base_dot_v1_game_183_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_southern_sotho_qa_multi_qa_mpnet_base_dot_v1_game_183_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_southern_sotho_qa_multi_qa_mpnet_base_dot_v1_game_183_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.0 MB|
+
+## References
+
+https://huggingface.co/abhijitt/bert_st_qa_multi-qa-mpnet-base-dot-v1_game_183
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bertoslav_limited_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-bertoslav_limited_pipeline_en.md
new file mode 100644
index 00000000000000..c5fbc5b2ce0b1f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bertoslav_limited_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bertoslav_limited_pipeline pipeline DistilBertEmbeddings from crabz
+author: John Snow Labs
+name: bertoslav_limited_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertoslav_limited_pipeline` is a English model originally trained by crabz.
+
+{:.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/bertoslav_limited_pipeline_en_5.5.0_3.0_1725775902337.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertoslav_limited_pipeline_en_5.5.0_3.0_1725775902337.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
+
+pipeline = PretrainedPipeline("bertoslav_limited_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bertoslav_limited_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bertoslav_limited_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/crabz/bertoslav-limited
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bertuit_3_a_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-bertuit_3_a_pipeline_en.md
new file mode 100644
index 00000000000000..e05d0c920b0b0f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bertuit_3_a_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bertuit_3_a_pipeline pipeline RoBertaForSequenceClassification from PEzquerra
+author: John Snow Labs
+name: bertuit_3_a_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertuit_3_a_pipeline` is a English model originally trained by PEzquerra.
+
+{:.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/bertuit_3_a_pipeline_en_5.5.0_3.0_1725821276822.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertuit_3_a_pipeline_en_5.5.0_3.0_1725821276822.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
+
+pipeline = PretrainedPipeline("bertuit_3_a_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bertuit_3_a_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bertuit_3_a_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/PEzquerra/BERTuit_3_A
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-best_model_yelp_polarity_16_13_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-best_model_yelp_polarity_16_13_pipeline_en.md
new file mode 100644
index 00000000000000..dafd70ddb10792
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-best_model_yelp_polarity_16_13_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English best_model_yelp_polarity_16_13_pipeline pipeline AlbertForSequenceClassification from simonycl
+author: John Snow Labs
+name: best_model_yelp_polarity_16_13_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`best_model_yelp_polarity_16_13_pipeline` is a English model originally trained by simonycl.
+
+{:.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/best_model_yelp_polarity_16_13_pipeline_en_5.5.0_3.0_1725767271580.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/best_model_yelp_polarity_16_13_pipeline_en_5.5.0_3.0_1725767271580.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
+
+pipeline = PretrainedPipeline("best_model_yelp_polarity_16_13_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("best_model_yelp_polarity_16_13_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|best_model_yelp_polarity_16_13_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/simonycl/best_model-yelp_polarity-16-13
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-best_model_yelp_polarity_32_21_en.md b/docs/_posts/ahmedlone127/2024-09-08-best_model_yelp_polarity_32_21_en.md
new file mode 100644
index 00000000000000..f1ff63739d2c7a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-best_model_yelp_polarity_32_21_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English best_model_yelp_polarity_32_21 AlbertForSequenceClassification from simonycl
+author: John Snow Labs
+name: best_model_yelp_polarity_32_21
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`best_model_yelp_polarity_32_21` is a English model originally trained by simonycl.
+
+{:.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/best_model_yelp_polarity_32_21_en_5.5.0_3.0_1725755797992.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/best_model_yelp_polarity_32_21_en_5.5.0_3.0_1725755797992.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("best_model_yelp_polarity_32_21","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("best_model_yelp_polarity_32_21", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|best_model_yelp_polarity_32_21|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/simonycl/best_model-yelp_polarity-32-21
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-best_model_yelp_polarity_32_21_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-best_model_yelp_polarity_32_21_pipeline_en.md
new file mode 100644
index 00000000000000..6043156ddf4f9b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-best_model_yelp_polarity_32_21_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English best_model_yelp_polarity_32_21_pipeline pipeline AlbertForSequenceClassification from simonycl
+author: John Snow Labs
+name: best_model_yelp_polarity_32_21_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`best_model_yelp_polarity_32_21_pipeline` is a English model originally trained by simonycl.
+
+{:.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/best_model_yelp_polarity_32_21_pipeline_en_5.5.0_3.0_1725755800276.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/best_model_yelp_polarity_32_21_pipeline_en_5.5.0_3.0_1725755800276.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
+
+pipeline = PretrainedPipeline("best_model_yelp_polarity_32_21_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("best_model_yelp_polarity_32_21_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|best_model_yelp_polarity_32_21_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/simonycl/best_model-yelp_polarity-32-21
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-best_model_yelp_polarity_64_87_en.md b/docs/_posts/ahmedlone127/2024-09-08-best_model_yelp_polarity_64_87_en.md
new file mode 100644
index 00000000000000..05f62b5404d9b8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-best_model_yelp_polarity_64_87_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English best_model_yelp_polarity_64_87 AlbertForSequenceClassification from simonycl
+author: John Snow Labs
+name: best_model_yelp_polarity_64_87
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`best_model_yelp_polarity_64_87` is a English model originally trained by simonycl.
+
+{:.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/best_model_yelp_polarity_64_87_en_5.5.0_3.0_1725767180270.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/best_model_yelp_polarity_64_87_en_5.5.0_3.0_1725767180270.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("best_model_yelp_polarity_64_87","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("best_model_yelp_polarity_64_87", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|best_model_yelp_polarity_64_87|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/simonycl/best_model-yelp_polarity-64-87
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bislama_all_bs160_allneg_finetuned_webnlg2020_relevance_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-bislama_all_bs160_allneg_finetuned_webnlg2020_relevance_pipeline_en.md
new file mode 100644
index 00000000000000..38c57bd557e021
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bislama_all_bs160_allneg_finetuned_webnlg2020_relevance_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English bislama_all_bs160_allneg_finetuned_webnlg2020_relevance_pipeline pipeline MPNetEmbeddings from teven
+author: John Snow Labs
+name: bislama_all_bs160_allneg_finetuned_webnlg2020_relevance_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bislama_all_bs160_allneg_finetuned_webnlg2020_relevance_pipeline` is a English model originally trained by teven.
+
+{:.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/bislama_all_bs160_allneg_finetuned_webnlg2020_relevance_pipeline_en_5.5.0_3.0_1725769896473.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bislama_all_bs160_allneg_finetuned_webnlg2020_relevance_pipeline_en_5.5.0_3.0_1725769896473.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
+
+pipeline = PretrainedPipeline("bislama_all_bs160_allneg_finetuned_webnlg2020_relevance_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bislama_all_bs160_allneg_finetuned_webnlg2020_relevance_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bislama_all_bs160_allneg_finetuned_webnlg2020_relevance_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.3 MB|
+
+## References
+
+https://huggingface.co/teven/bi_all_bs160_allneg_finetuned_WebNLG2020_relevance
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bislama_all_bs192_hardneg_finetuned_webnlg2020_data_coverage_en.md b/docs/_posts/ahmedlone127/2024-09-08-bislama_all_bs192_hardneg_finetuned_webnlg2020_data_coverage_en.md
new file mode 100644
index 00000000000000..4572b5f9063d3a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bislama_all_bs192_hardneg_finetuned_webnlg2020_data_coverage_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English bislama_all_bs192_hardneg_finetuned_webnlg2020_data_coverage MPNetEmbeddings from teven
+author: John Snow Labs
+name: bislama_all_bs192_hardneg_finetuned_webnlg2020_data_coverage
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`bislama_all_bs192_hardneg_finetuned_webnlg2020_data_coverage` is a English model originally trained by teven.
+
+{:.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/bislama_all_bs192_hardneg_finetuned_webnlg2020_data_coverage_en_5.5.0_3.0_1725817124093.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bislama_all_bs192_hardneg_finetuned_webnlg2020_data_coverage_en_5.5.0_3.0_1725817124093.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("bislama_all_bs192_hardneg_finetuned_webnlg2020_data_coverage","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("bislama_all_bs192_hardneg_finetuned_webnlg2020_data_coverage","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bislama_all_bs192_hardneg_finetuned_webnlg2020_data_coverage|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.3 MB|
+
+## References
+
+https://huggingface.co/teven/bi_all_bs192_hardneg_finetuned_WebNLG2020_data_coverage
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bleurt_base_128_en.md b/docs/_posts/ahmedlone127/2024-09-08-bleurt_base_128_en.md
new file mode 100644
index 00000000000000..fa876ac558ba11
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bleurt_base_128_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bleurt_base_128 BertForSequenceClassification from Elron
+author: John Snow Labs
+name: bleurt_base_128
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bleurt_base_128` is a English model originally trained by Elron.
+
+{:.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/bleurt_base_128_en_5.5.0_3.0_1725768131723.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bleurt_base_128_en_5.5.0_3.0_1725768131723.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bleurt_base_128","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bleurt_base_128", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bleurt_base_128|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.5 MB|
+
+## References
+
+https://huggingface.co/Elron/bleurt-base-128
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-boolq_microsoft_deberta_v3_base_seed_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-boolq_microsoft_deberta_v3_base_seed_2_pipeline_en.md
new file mode 100644
index 00000000000000..e5cd72ed724447
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-boolq_microsoft_deberta_v3_base_seed_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English boolq_microsoft_deberta_v3_base_seed_2_pipeline pipeline DeBertaForSequenceClassification from utahnlp
+author: John Snow Labs
+name: boolq_microsoft_deberta_v3_base_seed_2_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`boolq_microsoft_deberta_v3_base_seed_2_pipeline` is a English model originally trained by utahnlp.
+
+{:.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/boolq_microsoft_deberta_v3_base_seed_2_pipeline_en_5.5.0_3.0_1725811846072.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/boolq_microsoft_deberta_v3_base_seed_2_pipeline_en_5.5.0_3.0_1725811846072.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
+
+pipeline = PretrainedPipeline("boolq_microsoft_deberta_v3_base_seed_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("boolq_microsoft_deberta_v3_base_seed_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|boolq_microsoft_deberta_v3_base_seed_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|620.1 MB|
+
+## References
+
+https://huggingface.co/utahnlp/boolq_microsoft_deberta-v3-base_seed-2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-bot_train_amharic_7_en.md b/docs/_posts/ahmedlone127/2024-09-08-bot_train_amharic_7_en.md
new file mode 100644
index 00000000000000..b518d7072b461a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-bot_train_amharic_7_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bot_train_amharic_7 MarianTransformer from sisi
+author: John Snow Labs
+name: bot_train_amharic_7
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bot_train_amharic_7` is a English model originally trained by sisi.
+
+{:.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/bot_train_amharic_7_en_5.5.0_3.0_1725796197743.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bot_train_amharic_7_en_5.5.0_3.0_1725796197743.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("bot_train_amharic_7","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("bot_train_amharic_7","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bot_train_amharic_7|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|527.9 MB|
+
+## References
+
+https://huggingface.co/sisi/bot_train_am_7
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-brand_tone_of_voice_en.md b/docs/_posts/ahmedlone127/2024-09-08-brand_tone_of_voice_en.md
new file mode 100644
index 00000000000000..29698ba06386f5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-brand_tone_of_voice_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English brand_tone_of_voice BertForSequenceClassification from Oliver12315
+author: John Snow Labs
+name: brand_tone_of_voice
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`brand_tone_of_voice` is a English model originally trained by Oliver12315.
+
+{:.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/brand_tone_of_voice_en_5.5.0_3.0_1725839272083.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/brand_tone_of_voice_en_5.5.0_3.0_1725839272083.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("brand_tone_of_voice","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("brand_tone_of_voice", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|brand_tone_of_voice|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/Oliver12315/Brand_Tone_of_Voice
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-brand_tone_of_voice_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-brand_tone_of_voice_pipeline_en.md
new file mode 100644
index 00000000000000..b23d6afede67c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-brand_tone_of_voice_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English brand_tone_of_voice_pipeline pipeline BertForSequenceClassification from Oliver12315
+author: John Snow Labs
+name: brand_tone_of_voice_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`brand_tone_of_voice_pipeline` is a English model originally trained by Oliver12315.
+
+{:.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/brand_tone_of_voice_pipeline_en_5.5.0_3.0_1725839292491.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/brand_tone_of_voice_pipeline_en_5.5.0_3.0_1725839292491.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
+
+pipeline = PretrainedPipeline("brand_tone_of_voice_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("brand_tone_of_voice_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|brand_tone_of_voice_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/Oliver12315/Brand_Tone_of_Voice
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_model_aigurugaurav_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_model_aigurugaurav_en.md
new file mode 100644
index 00000000000000..f4d48060bdc1bb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_model_aigurugaurav_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_model_aigurugaurav DistilBertForSequenceClassification from aigurugaurav
+author: John Snow Labs
+name: burmese_awesome_model_aigurugaurav
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_aigurugaurav` is a English model originally trained by aigurugaurav.
+
+{:.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/burmese_awesome_model_aigurugaurav_en_5.5.0_3.0_1725777175900.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_aigurugaurav_en_5.5.0_3.0_1725777175900.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_aigurugaurav","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_aigurugaurav", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_aigurugaurav|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/aigurugaurav/my_awesome_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_model_jasper_lu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_model_jasper_lu_pipeline_en.md
new file mode 100644
index 00000000000000..c5f70b7d449242
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_model_jasper_lu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_jasper_lu_pipeline pipeline DistilBertForSequenceClassification from jasper-lu
+author: John Snow Labs
+name: burmese_awesome_model_jasper_lu_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_jasper_lu_pipeline` is a English model originally trained by jasper-lu.
+
+{:.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/burmese_awesome_model_jasper_lu_pipeline_en_5.5.0_3.0_1725809147303.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_jasper_lu_pipeline_en_5.5.0_3.0_1725809147303.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
+
+pipeline = PretrainedPipeline("burmese_awesome_model_jasper_lu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_jasper_lu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_jasper_lu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jasper-lu/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_model_maria01maria7_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_model_maria01maria7_pipeline_en.md
new file mode 100644
index 00000000000000..7661263cf05a17
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_model_maria01maria7_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_model_maria01maria7_pipeline pipeline DistilBertForSequenceClassification from maria01maria7
+author: John Snow Labs
+name: burmese_awesome_model_maria01maria7_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_maria01maria7_pipeline` is a English model originally trained by maria01maria7.
+
+{:.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/burmese_awesome_model_maria01maria7_pipeline_en_5.5.0_3.0_1725774978448.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_maria01maria7_pipeline_en_5.5.0_3.0_1725774978448.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
+
+pipeline = PretrainedPipeline("burmese_awesome_model_maria01maria7_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_model_maria01maria7_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_model_maria01maria7_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/maria01maria7/my_awesome_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model2_jvasdigital_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model2_jvasdigital_en.md
new file mode 100644
index 00000000000000..be941fd044dbd7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model2_jvasdigital_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model2_jvasdigital DistilBertForQuestionAnswering from jvasdigital
+author: John Snow Labs
+name: burmese_awesome_qa_model2_jvasdigital
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model2_jvasdigital` is a English model originally trained by jvasdigital.
+
+{:.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/burmese_awesome_qa_model2_jvasdigital_en_5.5.0_3.0_1725797949351.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model2_jvasdigital_en_5.5.0_3.0_1725797949351.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model2_jvasdigital","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model2_jvasdigital", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model2_jvasdigital|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/jvasdigital/my_awesome_qa_model2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_anhtu0811_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_anhtu0811_en.md
new file mode 100644
index 00000000000000..ea7415811499d3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_anhtu0811_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_anhtu0811 DistilBertForQuestionAnswering from Anhtu0811
+author: John Snow Labs
+name: burmese_awesome_qa_model_anhtu0811
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_anhtu0811` is a English model originally trained by Anhtu0811.
+
+{:.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/burmese_awesome_qa_model_anhtu0811_en_5.5.0_3.0_1725823461550.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_anhtu0811_en_5.5.0_3.0_1725823461550.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_anhtu0811","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_anhtu0811", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_anhtu0811|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Anhtu0811/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_anhtu0811_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_anhtu0811_pipeline_en.md
new file mode 100644
index 00000000000000..0a3c1a02226b34
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_anhtu0811_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_anhtu0811_pipeline pipeline DistilBertForQuestionAnswering from Anhtu0811
+author: John Snow Labs
+name: burmese_awesome_qa_model_anhtu0811_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_anhtu0811_pipeline` is a English model originally trained by Anhtu0811.
+
+{:.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/burmese_awesome_qa_model_anhtu0811_pipeline_en_5.5.0_3.0_1725823473608.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_anhtu0811_pipeline_en_5.5.0_3.0_1725823473608.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_anhtu0811_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_anhtu0811_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_anhtu0811_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Anhtu0811/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_atharva3101_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_atharva3101_en.md
new file mode 100644
index 00000000000000..d0c8a5b3d7793c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_atharva3101_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_atharva3101 DistilBertForQuestionAnswering from Atharva3101
+author: John Snow Labs
+name: burmese_awesome_qa_model_atharva3101
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_atharva3101` is a English model originally trained by Atharva3101.
+
+{:.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/burmese_awesome_qa_model_atharva3101_en_5.5.0_3.0_1725797917644.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_atharva3101_en_5.5.0_3.0_1725797917644.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_atharva3101","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_atharva3101", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_atharva3101|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Atharva3101/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_atharva3101_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_atharva3101_pipeline_en.md
new file mode 100644
index 00000000000000..38c8c4711b3c97
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_atharva3101_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_atharva3101_pipeline pipeline DistilBertForQuestionAnswering from Atharva3101
+author: John Snow Labs
+name: burmese_awesome_qa_model_atharva3101_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_atharva3101_pipeline` is a English model originally trained by Atharva3101.
+
+{:.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/burmese_awesome_qa_model_atharva3101_pipeline_en_5.5.0_3.0_1725797929817.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_atharva3101_pipeline_en_5.5.0_3.0_1725797929817.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_atharva3101_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_atharva3101_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_atharva3101_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Atharva3101/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_azyren_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_azyren_en.md
new file mode 100644
index 00000000000000..ff97b0cf2ecb56
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_azyren_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_azyren DistilBertForQuestionAnswering from Azyren
+author: John Snow Labs
+name: burmese_awesome_qa_model_azyren
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_azyren` is a English model originally trained by Azyren.
+
+{:.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/burmese_awesome_qa_model_azyren_en_5.5.0_3.0_1725823404118.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_azyren_en_5.5.0_3.0_1725823404118.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_azyren","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_azyren", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_azyren|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Azyren/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_azyren_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_azyren_pipeline_en.md
new file mode 100644
index 00000000000000..354e2ff01757b2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_azyren_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_azyren_pipeline pipeline DistilBertForQuestionAnswering from Azyren
+author: John Snow Labs
+name: burmese_awesome_qa_model_azyren_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_azyren_pipeline` is a English model originally trained by Azyren.
+
+{:.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/burmese_awesome_qa_model_azyren_pipeline_en_5.5.0_3.0_1725823415890.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_azyren_pipeline_en_5.5.0_3.0_1725823415890.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_azyren_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_azyren_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_azyren_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Azyren/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_carlodallaquercia_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_carlodallaquercia_en.md
new file mode 100644
index 00000000000000..49cf804599ba62
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_carlodallaquercia_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_carlodallaquercia DistilBertForQuestionAnswering from carlodallaquercia
+author: John Snow Labs
+name: burmese_awesome_qa_model_carlodallaquercia
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_carlodallaquercia` is a English model originally trained by carlodallaquercia.
+
+{:.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/burmese_awesome_qa_model_carlodallaquercia_en_5.5.0_3.0_1725798156911.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_carlodallaquercia_en_5.5.0_3.0_1725798156911.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_carlodallaquercia","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_carlodallaquercia", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_carlodallaquercia|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/carlodallaquercia/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_catbult_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_catbult_en.md
new file mode 100644
index 00000000000000..99fa074ee9de2a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_catbult_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_catbult DistilBertForQuestionAnswering from catbult
+author: John Snow Labs
+name: burmese_awesome_qa_model_catbult
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_catbult` is a English model originally trained by catbult.
+
+{:.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/burmese_awesome_qa_model_catbult_en_5.5.0_3.0_1725818525488.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_catbult_en_5.5.0_3.0_1725818525488.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_catbult","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_catbult", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_catbult|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/catbult/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_catbult_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_catbult_pipeline_en.md
new file mode 100644
index 00000000000000..279d970a770f27
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_catbult_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_catbult_pipeline pipeline DistilBertForQuestionAnswering from catbult
+author: John Snow Labs
+name: burmese_awesome_qa_model_catbult_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_catbult_pipeline` is a English model originally trained by catbult.
+
+{:.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/burmese_awesome_qa_model_catbult_pipeline_en_5.5.0_3.0_1725818540356.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_catbult_pipeline_en_5.5.0_3.0_1725818540356.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_catbult_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_catbult_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_catbult_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/catbult/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_charlie82_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_charlie82_en.md
new file mode 100644
index 00000000000000..3f022890e60597
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_charlie82_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_charlie82 DistilBertForQuestionAnswering from charlie82
+author: John Snow Labs
+name: burmese_awesome_qa_model_charlie82
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_charlie82` is a English model originally trained by charlie82.
+
+{:.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/burmese_awesome_qa_model_charlie82_en_5.5.0_3.0_1725823215587.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_charlie82_en_5.5.0_3.0_1725823215587.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_charlie82","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_charlie82", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_charlie82|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/charlie82/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_charlie82_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_charlie82_pipeline_en.md
new file mode 100644
index 00000000000000..2c5856069d7897
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_charlie82_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_charlie82_pipeline pipeline DistilBertForQuestionAnswering from charlie82
+author: John Snow Labs
+name: burmese_awesome_qa_model_charlie82_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_charlie82_pipeline` is a English model originally trained by charlie82.
+
+{:.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/burmese_awesome_qa_model_charlie82_pipeline_en_5.5.0_3.0_1725823228415.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_charlie82_pipeline_en_5.5.0_3.0_1725823228415.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_charlie82_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_charlie82_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_charlie82_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/charlie82/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_dark_magician_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_dark_magician_en.md
new file mode 100644
index 00000000000000..9c34617e4717c3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_dark_magician_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_dark_magician DistilBertForQuestionAnswering from Dark-magician
+author: John Snow Labs
+name: burmese_awesome_qa_model_dark_magician
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_dark_magician` is a English model originally trained by Dark-magician.
+
+{:.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/burmese_awesome_qa_model_dark_magician_en_5.5.0_3.0_1725798587201.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_dark_magician_en_5.5.0_3.0_1725798587201.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_dark_magician","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_dark_magician", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_dark_magician|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Dark-magician/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_dark_magician_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_dark_magician_pipeline_en.md
new file mode 100644
index 00000000000000..dcde07c4d6ca9d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_dark_magician_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_dark_magician_pipeline pipeline DistilBertForQuestionAnswering from Dark-magician
+author: John Snow Labs
+name: burmese_awesome_qa_model_dark_magician_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_dark_magician_pipeline` is a English model originally trained by Dark-magician.
+
+{:.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/burmese_awesome_qa_model_dark_magician_pipeline_en_5.5.0_3.0_1725798598615.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_dark_magician_pipeline_en_5.5.0_3.0_1725798598615.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_dark_magician_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_dark_magician_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_dark_magician_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Dark-magician/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_ellascheltinga_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_ellascheltinga_en.md
new file mode 100644
index 00000000000000..faf875c4857005
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_ellascheltinga_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_ellascheltinga DistilBertForQuestionAnswering from EllaScheltinga
+author: John Snow Labs
+name: burmese_awesome_qa_model_ellascheltinga
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_ellascheltinga` is a English model originally trained by EllaScheltinga.
+
+{:.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/burmese_awesome_qa_model_ellascheltinga_en_5.5.0_3.0_1725798654881.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_ellascheltinga_en_5.5.0_3.0_1725798654881.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_ellascheltinga","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_ellascheltinga", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_ellascheltinga|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/EllaScheltinga/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_ellascheltinga_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_ellascheltinga_pipeline_en.md
new file mode 100644
index 00000000000000..d88cb91563b2da
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_ellascheltinga_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_ellascheltinga_pipeline pipeline DistilBertForQuestionAnswering from EllaScheltinga
+author: John Snow Labs
+name: burmese_awesome_qa_model_ellascheltinga_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_ellascheltinga_pipeline` is a English model originally trained by EllaScheltinga.
+
+{:.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/burmese_awesome_qa_model_ellascheltinga_pipeline_en_5.5.0_3.0_1725798666432.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_ellascheltinga_pipeline_en_5.5.0_3.0_1725798666432.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_ellascheltinga_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_ellascheltinga_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_ellascheltinga_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/EllaScheltinga/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_huiziy_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_huiziy_pipeline_en.md
new file mode 100644
index 00000000000000..301f2b02a464ab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_huiziy_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_huiziy_pipeline pipeline DistilBertForQuestionAnswering from huiziy
+author: John Snow Labs
+name: burmese_awesome_qa_model_huiziy_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_huiziy_pipeline` is a English model originally trained by huiziy.
+
+{:.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/burmese_awesome_qa_model_huiziy_pipeline_en_5.5.0_3.0_1725823382468.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_huiziy_pipeline_en_5.5.0_3.0_1725823382468.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_huiziy_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_huiziy_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_huiziy_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/huiziy/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_jhhan_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_jhhan_en.md
new file mode 100644
index 00000000000000..524b7431c2a8dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_jhhan_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_jhhan DistilBertForQuestionAnswering from JHhan
+author: John Snow Labs
+name: burmese_awesome_qa_model_jhhan
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_jhhan` is a English model originally trained by JHhan.
+
+{:.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/burmese_awesome_qa_model_jhhan_en_5.5.0_3.0_1725818711660.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_jhhan_en_5.5.0_3.0_1725818711660.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_jhhan","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_jhhan", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_jhhan|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/JHhan/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_lavanyam_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_lavanyam_en.md
new file mode 100644
index 00000000000000..1dd385b172bfd3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_lavanyam_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_lavanyam DistilBertForQuestionAnswering from LavanyaM
+author: John Snow Labs
+name: burmese_awesome_qa_model_lavanyam
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_lavanyam` is a English model originally trained by LavanyaM.
+
+{:.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/burmese_awesome_qa_model_lavanyam_en_5.5.0_3.0_1725817998879.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_lavanyam_en_5.5.0_3.0_1725817998879.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_lavanyam","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_lavanyam", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_lavanyam|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/LavanyaM/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_lavanyam_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_lavanyam_pipeline_en.md
new file mode 100644
index 00000000000000..7a2d6f6310ce44
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_lavanyam_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_lavanyam_pipeline pipeline DistilBertForQuestionAnswering from LavanyaM
+author: John Snow Labs
+name: burmese_awesome_qa_model_lavanyam_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_lavanyam_pipeline` is a English model originally trained by LavanyaM.
+
+{:.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/burmese_awesome_qa_model_lavanyam_pipeline_en_5.5.0_3.0_1725818013571.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_lavanyam_pipeline_en_5.5.0_3.0_1725818013571.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_lavanyam_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_lavanyam_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_lavanyam_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/LavanyaM/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_mac999_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_mac999_pipeline_en.md
new file mode 100644
index 00000000000000..6f0b025e5a61d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_mac999_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_mac999_pipeline pipeline DistilBertForQuestionAnswering from mac999
+author: John Snow Labs
+name: burmese_awesome_qa_model_mac999_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_mac999_pipeline` is a English model originally trained by mac999.
+
+{:.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/burmese_awesome_qa_model_mac999_pipeline_en_5.5.0_3.0_1725823106629.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_mac999_pipeline_en_5.5.0_3.0_1725823106629.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_mac999_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_mac999_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_mac999_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/mac999/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_marzottialessia_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_marzottialessia_en.md
new file mode 100644
index 00000000000000..b1830b9e6e014d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_marzottialessia_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_marzottialessia DistilBertForQuestionAnswering from MarzottiAlessia
+author: John Snow Labs
+name: burmese_awesome_qa_model_marzottialessia
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_marzottialessia` is a English model originally trained by MarzottiAlessia.
+
+{:.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/burmese_awesome_qa_model_marzottialessia_en_5.5.0_3.0_1725818285618.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_marzottialessia_en_5.5.0_3.0_1725818285618.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_marzottialessia","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_marzottialessia", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_marzottialessia|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/MarzottiAlessia/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_marzottialessia_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_marzottialessia_pipeline_en.md
new file mode 100644
index 00000000000000..009d134fa25c28
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_marzottialessia_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_marzottialessia_pipeline pipeline DistilBertForQuestionAnswering from MarzottiAlessia
+author: John Snow Labs
+name: burmese_awesome_qa_model_marzottialessia_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_marzottialessia_pipeline` is a English model originally trained by MarzottiAlessia.
+
+{:.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/burmese_awesome_qa_model_marzottialessia_pipeline_en_5.5.0_3.0_1725818297810.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_marzottialessia_pipeline_en_5.5.0_3.0_1725818297810.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_marzottialessia_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_marzottialessia_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_marzottialessia_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/MarzottiAlessia/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_nkey1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_nkey1_pipeline_en.md
new file mode 100644
index 00000000000000..7889fe7e88c969
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_nkey1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_nkey1_pipeline pipeline DistilBertForQuestionAnswering from nkey1
+author: John Snow Labs
+name: burmese_awesome_qa_model_nkey1_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_nkey1_pipeline` is a English model originally trained by nkey1.
+
+{:.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/burmese_awesome_qa_model_nkey1_pipeline_en_5.5.0_3.0_1725823211220.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_nkey1_pipeline_en_5.5.0_3.0_1725823211220.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_nkey1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_nkey1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_nkey1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/nkey1/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_rahul13_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_rahul13_en.md
new file mode 100644
index 00000000000000..d5f8d0435154ab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_rahul13_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_rahul13 DistilBertForQuestionAnswering from Rahul13
+author: John Snow Labs
+name: burmese_awesome_qa_model_rahul13
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_rahul13` is a English model originally trained by Rahul13.
+
+{:.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/burmese_awesome_qa_model_rahul13_en_5.5.0_3.0_1725798475208.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_rahul13_en_5.5.0_3.0_1725798475208.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_rahul13","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_rahul13", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_rahul13|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Rahul13/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_saekbote_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_saekbote_en.md
new file mode 100644
index 00000000000000..63b809c1d0ba71
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_saekbote_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_saekbote DistilBertForQuestionAnswering from saekbote
+author: John Snow Labs
+name: burmese_awesome_qa_model_saekbote
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_saekbote` is a English model originally trained by saekbote.
+
+{:.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/burmese_awesome_qa_model_saekbote_en_5.5.0_3.0_1725798340653.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_saekbote_en_5.5.0_3.0_1725798340653.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_saekbote","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_saekbote", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_saekbote|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/saekbote/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_saekbote_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_saekbote_pipeline_en.md
new file mode 100644
index 00000000000000..6d02d409bdc80e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_saekbote_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_saekbote_pipeline pipeline DistilBertForQuestionAnswering from saekbote
+author: John Snow Labs
+name: burmese_awesome_qa_model_saekbote_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_saekbote_pipeline` is a English model originally trained by saekbote.
+
+{:.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/burmese_awesome_qa_model_saekbote_pipeline_en_5.5.0_3.0_1725798353113.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_saekbote_pipeline_en_5.5.0_3.0_1725798353113.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_saekbote_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_saekbote_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_saekbote_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/saekbote/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_saty2hoty_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_saty2hoty_en.md
new file mode 100644
index 00000000000000..bcd4078a96a361
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_saty2hoty_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_saty2hoty DistilBertForQuestionAnswering from Saty2hoty
+author: John Snow Labs
+name: burmese_awesome_qa_model_saty2hoty
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_saty2hoty` is a English model originally trained by Saty2hoty.
+
+{:.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/burmese_awesome_qa_model_saty2hoty_en_5.5.0_3.0_1725797918121.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_saty2hoty_en_5.5.0_3.0_1725797918121.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_saty2hoty","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_saty2hoty", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_saty2hoty|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Saty2hoty/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_saty2hoty_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_saty2hoty_pipeline_en.md
new file mode 100644
index 00000000000000..3696209f9dcc83
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_saty2hoty_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_saty2hoty_pipeline pipeline DistilBertForQuestionAnswering from Saty2hoty
+author: John Snow Labs
+name: burmese_awesome_qa_model_saty2hoty_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_saty2hoty_pipeline` is a English model originally trained by Saty2hoty.
+
+{:.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/burmese_awesome_qa_model_saty2hoty_pipeline_en_5.5.0_3.0_1725797931238.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_saty2hoty_pipeline_en_5.5.0_3.0_1725797931238.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_saty2hoty_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_saty2hoty_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_saty2hoty_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Saty2hoty/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_snachda_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_snachda_en.md
new file mode 100644
index 00000000000000..a28141295da697
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_snachda_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_snachda DistilBertForQuestionAnswering from snachDA
+author: John Snow Labs
+name: burmese_awesome_qa_model_snachda
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_snachda` is a English model originally trained by snachDA.
+
+{:.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/burmese_awesome_qa_model_snachda_en_5.5.0_3.0_1725823632847.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_snachda_en_5.5.0_3.0_1725823632847.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_snachda","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_snachda", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_snachda|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/snachDA/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_snachda_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_snachda_pipeline_en.md
new file mode 100644
index 00000000000000..68e5bb8aba3301
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_snachda_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_snachda_pipeline pipeline DistilBertForQuestionAnswering from snachDA
+author: John Snow Labs
+name: burmese_awesome_qa_model_snachda_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_snachda_pipeline` is a English model originally trained by snachDA.
+
+{:.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/burmese_awesome_qa_model_snachda_pipeline_en_5.5.0_3.0_1725823644619.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_snachda_pipeline_en_5.5.0_3.0_1725823644619.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_snachda_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_snachda_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_snachda_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/snachDA/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_ukson_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_ukson_en.md
new file mode 100644
index 00000000000000..c1ba521e0be5fe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_ukson_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_ukson DistilBertForQuestionAnswering from ukson
+author: John Snow Labs
+name: burmese_awesome_qa_model_ukson
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_ukson` is a English model originally trained by ukson.
+
+{:.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/burmese_awesome_qa_model_ukson_en_5.5.0_3.0_1725798034938.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_ukson_en_5.5.0_3.0_1725798034938.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_ukson","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_ukson", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_ukson|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/ukson/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_ukson_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_ukson_pipeline_en.md
new file mode 100644
index 00000000000000..3b9c28dd503faa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_ukson_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_ukson_pipeline pipeline DistilBertForQuestionAnswering from ukson
+author: John Snow Labs
+name: burmese_awesome_qa_model_ukson_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_ukson_pipeline` is a English model originally trained by ukson.
+
+{:.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/burmese_awesome_qa_model_ukson_pipeline_en_5.5.0_3.0_1725798048705.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_ukson_pipeline_en_5.5.0_3.0_1725798048705.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_ukson_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_ukson_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_ukson_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/ukson/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_wcywong_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_wcywong_en.md
new file mode 100644
index 00000000000000..620e07946ae6ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_wcywong_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_wcywong DistilBertForQuestionAnswering from wcywong
+author: John Snow Labs
+name: burmese_awesome_qa_model_wcywong
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_wcywong` is a English model originally trained by wcywong.
+
+{:.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/burmese_awesome_qa_model_wcywong_en_5.5.0_3.0_1725818152223.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_wcywong_en_5.5.0_3.0_1725818152223.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_wcywong","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_wcywong", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_wcywong|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/wcywong/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_wcywong_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_wcywong_pipeline_en.md
new file mode 100644
index 00000000000000..665a87a799d8bb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_wcywong_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_wcywong_pipeline pipeline DistilBertForQuestionAnswering from wcywong
+author: John Snow Labs
+name: burmese_awesome_qa_model_wcywong_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_wcywong_pipeline` is a English model originally trained by wcywong.
+
+{:.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/burmese_awesome_qa_model_wcywong_pipeline_en_5.5.0_3.0_1725818164679.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_wcywong_pipeline_en_5.5.0_3.0_1725818164679.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_wcywong_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_wcywong_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_wcywong_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/wcywong/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_xbotwovenware_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_xbotwovenware_pipeline_en.md
new file mode 100644
index 00000000000000..30b1fb19c576f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_xbotwovenware_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_xbotwovenware_pipeline pipeline DistilBertForQuestionAnswering from xbotwovenware
+author: John Snow Labs
+name: burmese_awesome_qa_model_xbotwovenware_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_xbotwovenware_pipeline` is a English model originally trained by xbotwovenware.
+
+{:.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/burmese_awesome_qa_model_xbotwovenware_pipeline_en_5.5.0_3.0_1725823205891.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_xbotwovenware_pipeline_en_5.5.0_3.0_1725823205891.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_xbotwovenware_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_xbotwovenware_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_xbotwovenware_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/xbotwovenware/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_zhandsome_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_zhandsome_en.md
new file mode 100644
index 00000000000000..8aeb84d6d04674
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_qa_model_zhandsome_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_zhandsome DistilBertForQuestionAnswering from zhandsome
+author: John Snow Labs
+name: burmese_awesome_qa_model_zhandsome
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_zhandsome` is a English model originally trained by zhandsome.
+
+{:.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/burmese_awesome_qa_model_zhandsome_en_5.5.0_3.0_1725823504368.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_zhandsome_en_5.5.0_3.0_1725823504368.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_zhandsome","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_zhandsome", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_zhandsome|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/zhandsome/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_setfit_model3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_setfit_model3_pipeline_en.md
new file mode 100644
index 00000000000000..399fb3ed37ad7b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_setfit_model3_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_setfit_model3_pipeline pipeline MPNetEmbeddings from ilhkn
+author: John Snow Labs
+name: burmese_awesome_setfit_model3_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_setfit_model3_pipeline` is a English model originally trained by ilhkn.
+
+{:.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/burmese_awesome_setfit_model3_pipeline_en_5.5.0_3.0_1725815797036.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model3_pipeline_en_5.5.0_3.0_1725815797036.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
+
+pipeline = PretrainedPipeline("burmese_awesome_setfit_model3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_setfit_model3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_setfit_model3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/ilhkn/my-awesome-setfit-model3
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_setfit_model4_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_setfit_model4_en.md
new file mode 100644
index 00000000000000..4d9c96140cb0f5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_setfit_model4_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_setfit_model4 MPNetEmbeddings from maustin10
+author: John Snow Labs
+name: burmese_awesome_setfit_model4
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`burmese_awesome_setfit_model4` is a English model originally trained by maustin10.
+
+{:.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/burmese_awesome_setfit_model4_en_5.5.0_3.0_1725816185528.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model4_en_5.5.0_3.0_1725816185528.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("burmese_awesome_setfit_model4","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("burmese_awesome_setfit_model4","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_setfit_model4|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/maustin10/my-awesome-setfit-model4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_setfit_model_chadeh_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_setfit_model_chadeh_en.md
new file mode 100644
index 00000000000000..0d80923d945074
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_setfit_model_chadeh_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_setfit_model_chadeh MPNetEmbeddings from Chadeh
+author: John Snow Labs
+name: burmese_awesome_setfit_model_chadeh
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`burmese_awesome_setfit_model_chadeh` is a English model originally trained by Chadeh.
+
+{:.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/burmese_awesome_setfit_model_chadeh_en_5.5.0_3.0_1725817713479.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_chadeh_en_5.5.0_3.0_1725817713479.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("burmese_awesome_setfit_model_chadeh","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("burmese_awesome_setfit_model_chadeh","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_setfit_model_chadeh|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/Chadeh/my-awesome-setfit-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_setfit_model_cjos_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_setfit_model_cjos_en.md
new file mode 100644
index 00000000000000..8a604ea814170f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_setfit_model_cjos_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_setfit_model_cjos MPNetEmbeddings from cjos
+author: John Snow Labs
+name: burmese_awesome_setfit_model_cjos
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`burmese_awesome_setfit_model_cjos` is a English model originally trained by cjos.
+
+{:.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/burmese_awesome_setfit_model_cjos_en_5.5.0_3.0_1725816556080.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_cjos_en_5.5.0_3.0_1725816556080.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("burmese_awesome_setfit_model_cjos","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("burmese_awesome_setfit_model_cjos","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_setfit_model_cjos|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/cjos/my-awesome-setfit-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_setfit_model_cjos_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_setfit_model_cjos_pipeline_en.md
new file mode 100644
index 00000000000000..184c08ee41a757
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_setfit_model_cjos_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_setfit_model_cjos_pipeline pipeline MPNetEmbeddings from cjos
+author: John Snow Labs
+name: burmese_awesome_setfit_model_cjos_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_setfit_model_cjos_pipeline` is a English model originally trained by cjos.
+
+{:.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/burmese_awesome_setfit_model_cjos_pipeline_en_5.5.0_3.0_1725816585799.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_cjos_pipeline_en_5.5.0_3.0_1725816585799.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
+
+pipeline = PretrainedPipeline("burmese_awesome_setfit_model_cjos_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_setfit_model_cjos_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_setfit_model_cjos_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/cjos/my-awesome-setfit-model
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_setfit_model_leerobert_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_setfit_model_leerobert_en.md
new file mode 100644
index 00000000000000..83758004104cbc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_setfit_model_leerobert_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_setfit_model_leerobert MPNetEmbeddings from leerobert
+author: John Snow Labs
+name: burmese_awesome_setfit_model_leerobert
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`burmese_awesome_setfit_model_leerobert` is a English model originally trained by leerobert.
+
+{:.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/burmese_awesome_setfit_model_leerobert_en_5.5.0_3.0_1725817634909.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_leerobert_en_5.5.0_3.0_1725817634909.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("burmese_awesome_setfit_model_leerobert","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("burmese_awesome_setfit_model_leerobert","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_setfit_model_leerobert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.0 MB|
+
+## References
+
+https://huggingface.co/leerobert/my-awesome-setfit-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_setfit_model_leerobert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_setfit_model_leerobert_pipeline_en.md
new file mode 100644
index 00000000000000..5a6567c59d0785
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_setfit_model_leerobert_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_setfit_model_leerobert_pipeline pipeline MPNetEmbeddings from leerobert
+author: John Snow Labs
+name: burmese_awesome_setfit_model_leerobert_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_setfit_model_leerobert_pipeline` is a English model originally trained by leerobert.
+
+{:.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/burmese_awesome_setfit_model_leerobert_pipeline_en_5.5.0_3.0_1725817655116.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_setfit_model_leerobert_pipeline_en_5.5.0_3.0_1725817655116.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
+
+pipeline = PretrainedPipeline("burmese_awesome_setfit_model_leerobert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_setfit_model_leerobert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_setfit_model_leerobert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.0 MB|
+
+## References
+
+https://huggingface.co/leerobert/my-awesome-setfit-model
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_jhs_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_jhs_en.md
new file mode 100644
index 00000000000000..0649d16fbf62ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_jhs_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_jhs DistilBertForTokenClassification from gonzalezrostani
+author: John Snow Labs
+name: burmese_awesome_wnut_jhs
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_jhs` is a English model originally trained by gonzalezrostani.
+
+{:.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/burmese_awesome_wnut_jhs_en_5.5.0_3.0_1725827374696.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_jhs_en_5.5.0_3.0_1725827374696.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_jhs","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_jhs", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_jhs|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/gonzalezrostani/my_awesome_wnut_JHs
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_jhs_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_jhs_pipeline_en.md
new file mode 100644
index 00000000000000..68edd1aeaaf8e5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_jhs_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_jhs_pipeline pipeline DistilBertForTokenClassification from gonzalezrostani
+author: John Snow Labs
+name: burmese_awesome_wnut_jhs_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_jhs_pipeline` is a English model originally trained by gonzalezrostani.
+
+{:.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/burmese_awesome_wnut_jhs_pipeline_en_5.5.0_3.0_1725827391799.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_jhs_pipeline_en_5.5.0_3.0_1725827391799.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
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_jhs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_jhs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_jhs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/gonzalezrostani/my_awesome_wnut_JHs
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_abishines_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_abishines_pipeline_en.md
new file mode 100644
index 00000000000000..2543100b2bbbaa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_abishines_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_abishines_pipeline pipeline DistilBertForTokenClassification from abishines
+author: John Snow Labs
+name: burmese_awesome_wnut_model_abishines_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_abishines_pipeline` is a English model originally trained by abishines.
+
+{:.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/burmese_awesome_wnut_model_abishines_pipeline_en_5.5.0_3.0_1725827505402.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_abishines_pipeline_en_5.5.0_3.0_1725827505402.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
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_abishines_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_abishines_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_abishines_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/abishines/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_alexandryte6_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_alexandryte6_pipeline_en.md
new file mode 100644
index 00000000000000..9f28d54721c4e2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_alexandryte6_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_alexandryte6_pipeline pipeline DistilBertForTokenClassification from alexandryte6
+author: John Snow Labs
+name: burmese_awesome_wnut_model_alexandryte6_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_alexandryte6_pipeline` is a English model originally trained by alexandryte6.
+
+{:.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/burmese_awesome_wnut_model_alexandryte6_pipeline_en_5.5.0_3.0_1725788871683.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_alexandryte6_pipeline_en_5.5.0_3.0_1725788871683.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
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_alexandryte6_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_alexandryte6_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_alexandryte6_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/alexandryte6/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_caseyf_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_caseyf_en.md
new file mode 100644
index 00000000000000..f6a13e6739e24b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_caseyf_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_caseyf DistilBertForTokenClassification from CaseyF
+author: John Snow Labs
+name: burmese_awesome_wnut_model_caseyf
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_caseyf` is a English model originally trained by CaseyF.
+
+{:.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/burmese_awesome_wnut_model_caseyf_en_5.5.0_3.0_1725827374667.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_caseyf_en_5.5.0_3.0_1725827374667.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_caseyf","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_caseyf", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_caseyf|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/CaseyF/my-awesome-wnut-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_cwchang_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_cwchang_en.md
new file mode 100644
index 00000000000000..7456c256a483bb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_cwchang_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_cwchang DistilBertForTokenClassification from cwchang
+author: John Snow Labs
+name: burmese_awesome_wnut_model_cwchang
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_cwchang` is a English model originally trained by cwchang.
+
+{:.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/burmese_awesome_wnut_model_cwchang_en_5.5.0_3.0_1725789028179.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_cwchang_en_5.5.0_3.0_1725789028179.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_cwchang","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_cwchang", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_cwchang|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/cwchang/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_diegofsngoog_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_diegofsngoog_en.md
new file mode 100644
index 00000000000000..bf05191a6145c3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_diegofsngoog_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_diegofsngoog DistilBertForTokenClassification from diegofsngoog
+author: John Snow Labs
+name: burmese_awesome_wnut_model_diegofsngoog
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_diegofsngoog` is a English model originally trained by diegofsngoog.
+
+{:.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/burmese_awesome_wnut_model_diegofsngoog_en_5.5.0_3.0_1725788461603.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_diegofsngoog_en_5.5.0_3.0_1725788461603.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_diegofsngoog","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_diegofsngoog", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_diegofsngoog|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/diegofsngoog/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_jaepax_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_jaepax_en.md
new file mode 100644
index 00000000000000..6ee7a0986e01d7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_jaepax_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_jaepax DistilBertForTokenClassification from JaepaX
+author: John Snow Labs
+name: burmese_awesome_wnut_model_jaepax
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_jaepax` is a English model originally trained by JaepaX.
+
+{:.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/burmese_awesome_wnut_model_jaepax_en_5.5.0_3.0_1725837205868.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_jaepax_en_5.5.0_3.0_1725837205868.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_jaepax","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_jaepax", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_jaepax|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/JaepaX/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_janis332_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_janis332_en.md
new file mode 100644
index 00000000000000..78a264d0abcefa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_janis332_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_janis332 DistilBertForTokenClassification from janis332
+author: John Snow Labs
+name: burmese_awesome_wnut_model_janis332
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_janis332` is a English model originally trained by janis332.
+
+{:.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/burmese_awesome_wnut_model_janis332_en_5.5.0_3.0_1725827623652.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_janis332_en_5.5.0_3.0_1725827623652.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_janis332","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_janis332", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_janis332|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/janis332/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_massiaz_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_massiaz_en.md
new file mode 100644
index 00000000000000..a6258d1a3ebf12
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_massiaz_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_massiaz DistilBertForTokenClassification from massiaz
+author: John Snow Labs
+name: burmese_awesome_wnut_model_massiaz
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_massiaz` is a English model originally trained by massiaz.
+
+{:.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/burmese_awesome_wnut_model_massiaz_en_5.5.0_3.0_1725788530466.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_massiaz_en_5.5.0_3.0_1725788530466.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_massiaz","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_massiaz", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_massiaz|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/massiaz/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_meghtedari_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_meghtedari_en.md
new file mode 100644
index 00000000000000..eba9784d7fd456
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_meghtedari_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_meghtedari DistilBertForTokenClassification from meghtedari
+author: John Snow Labs
+name: burmese_awesome_wnut_model_meghtedari
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_meghtedari` is a English model originally trained by meghtedari.
+
+{:.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/burmese_awesome_wnut_model_meghtedari_en_5.5.0_3.0_1725827591610.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_meghtedari_en_5.5.0_3.0_1725827591610.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_meghtedari","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_meghtedari", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_meghtedari|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/meghtedari/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_meghtedari_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_meghtedari_pipeline_en.md
new file mode 100644
index 00000000000000..1d3c2f847f61b8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_meghtedari_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_meghtedari_pipeline pipeline DistilBertForTokenClassification from meghtedari
+author: John Snow Labs
+name: burmese_awesome_wnut_model_meghtedari_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_meghtedari_pipeline` is a English model originally trained by meghtedari.
+
+{:.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/burmese_awesome_wnut_model_meghtedari_pipeline_en_5.5.0_3.0_1725827603235.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_meghtedari_pipeline_en_5.5.0_3.0_1725827603235.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
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_meghtedari_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_meghtedari_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_meghtedari_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/meghtedari/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_pushokay_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_pushokay_en.md
new file mode 100644
index 00000000000000..6909767e7d73f8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_pushokay_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_pushokay DistilBertForTokenClassification from pushokay
+author: John Snow Labs
+name: burmese_awesome_wnut_model_pushokay
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_pushokay` is a English model originally trained by pushokay.
+
+{:.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/burmese_awesome_wnut_model_pushokay_en_5.5.0_3.0_1725827704335.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_pushokay_en_5.5.0_3.0_1725827704335.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_pushokay","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_pushokay", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_pushokay|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/pushokay/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_pushokay_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_pushokay_pipeline_en.md
new file mode 100644
index 00000000000000..8e9e1bf9ac1621
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_pushokay_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_pushokay_pipeline pipeline DistilBertForTokenClassification from pushokay
+author: John Snow Labs
+name: burmese_awesome_wnut_model_pushokay_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_pushokay_pipeline` is a English model originally trained by pushokay.
+
+{:.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/burmese_awesome_wnut_model_pushokay_pipeline_en_5.5.0_3.0_1725827716674.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_pushokay_pipeline_en_5.5.0_3.0_1725827716674.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
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_pushokay_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_pushokay_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_pushokay_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/pushokay/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_saidileep1007_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_saidileep1007_pipeline_en.md
new file mode 100644
index 00000000000000..cbf559ebb73afe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_saidileep1007_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_saidileep1007_pipeline pipeline DistilBertForTokenClassification from saidileep1007
+author: John Snow Labs
+name: burmese_awesome_wnut_model_saidileep1007_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_saidileep1007_pipeline` is a English model originally trained by saidileep1007.
+
+{:.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/burmese_awesome_wnut_model_saidileep1007_pipeline_en_5.5.0_3.0_1725788571672.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_saidileep1007_pipeline_en_5.5.0_3.0_1725788571672.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
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_saidileep1007_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_saidileep1007_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_saidileep1007_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/saidileep1007/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_sarahh23_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_sarahh23_en.md
new file mode 100644
index 00000000000000..cd684dabb44b5c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_sarahh23_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_sarahh23 DistilBertForTokenClassification from sarahh23
+author: John Snow Labs
+name: burmese_awesome_wnut_model_sarahh23
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_sarahh23` is a English model originally trained by sarahh23.
+
+{:.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/burmese_awesome_wnut_model_sarahh23_en_5.5.0_3.0_1725828081395.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_sarahh23_en_5.5.0_3.0_1725828081395.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_sarahh23","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_sarahh23", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_sarahh23|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/sarahh23/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_sarahh23_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_sarahh23_pipeline_en.md
new file mode 100644
index 00000000000000..ed1c42f0c8a879
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_sarahh23_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_sarahh23_pipeline pipeline DistilBertForTokenClassification from sarahh23
+author: John Snow Labs
+name: burmese_awesome_wnut_model_sarahh23_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_sarahh23_pipeline` is a English model originally trained by sarahh23.
+
+{:.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/burmese_awesome_wnut_model_sarahh23_pipeline_en_5.5.0_3.0_1725828092905.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_sarahh23_pipeline_en_5.5.0_3.0_1725828092905.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
+
+pipeline = PretrainedPipeline("burmese_awesome_wnut_model_sarahh23_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_wnut_model_sarahh23_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_sarahh23_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/sarahh23/my_awesome_wnut_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_sjtukai_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_sjtukai_en.md
new file mode 100644
index 00000000000000..114b6f67f3696d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_awesome_wnut_model_sjtukai_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_sjtukai DistilBertForTokenClassification from sjtukai
+author: John Snow Labs
+name: burmese_awesome_wnut_model_sjtukai
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_sjtukai` is a English model originally trained by sjtukai.
+
+{:.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/burmese_awesome_wnut_model_sjtukai_en_5.5.0_3.0_1725788769985.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_sjtukai_en_5.5.0_3.0_1725788769985.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_sjtukai","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_sjtukai", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_sjtukai|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/sjtukai/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_first_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_first_model_pipeline_en.md
new file mode 100644
index 00000000000000..431f5034fa819f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_first_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_first_model_pipeline pipeline CamemBertEmbeddings from hippoleveque
+author: John Snow Labs
+name: burmese_first_model_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_first_model_pipeline` is a English model originally trained by hippoleveque.
+
+{:.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/burmese_first_model_pipeline_en_5.5.0_3.0_1725836390445.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_first_model_pipeline_en_5.5.0_3.0_1725836390445.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
+
+pipeline = PretrainedPipeline("burmese_first_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_first_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_first_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/hippoleveque/my-first-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_ner_model_yadvi_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_ner_model_yadvi_en.md
new file mode 100644
index 00000000000000..13b3bd97a7835f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_ner_model_yadvi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_ner_model_yadvi DistilBertForTokenClassification from yadvi
+author: John Snow Labs
+name: burmese_ner_model_yadvi
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_ner_model_yadvi` is a English model originally trained by yadvi.
+
+{:.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/burmese_ner_model_yadvi_en_5.5.0_3.0_1725789085452.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_ner_model_yadvi_en_5.5.0_3.0_1725789085452.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_ner_model_yadvi","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_ner_model_yadvi", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_ner_model_yadvi|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/yadvi/my_ner_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_ws_extraction_model_27th_mar_2_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_ws_extraction_model_27th_mar_2_en.md
new file mode 100644
index 00000000000000..ced6a9ee9d0e09
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_ws_extraction_model_27th_mar_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_ws_extraction_model_27th_mar_2 DistilBertForTokenClassification from manimaranpa07
+author: John Snow Labs
+name: burmese_ws_extraction_model_27th_mar_2
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_ws_extraction_model_27th_mar_2` is a English model originally trained by manimaranpa07.
+
+{:.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/burmese_ws_extraction_model_27th_mar_2_en_5.5.0_3.0_1725788553617.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_ws_extraction_model_27th_mar_2_en_5.5.0_3.0_1725788553617.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_ws_extraction_model_27th_mar_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_ws_extraction_model_27th_mar_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_ws_extraction_model_27th_mar_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/manimaranpa07/my_Ws_extraction_model_27th_mar_2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-burmese_ws_extraction_model_27th_mar_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-burmese_ws_extraction_model_27th_mar_2_pipeline_en.md
new file mode 100644
index 00000000000000..3a97824aa64085
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-burmese_ws_extraction_model_27th_mar_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English burmese_ws_extraction_model_27th_mar_2_pipeline pipeline DistilBertForTokenClassification from manimaranpa07
+author: John Snow Labs
+name: burmese_ws_extraction_model_27th_mar_2_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_ws_extraction_model_27th_mar_2_pipeline` is a English model originally trained by manimaranpa07.
+
+{:.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/burmese_ws_extraction_model_27th_mar_2_pipeline_en_5.5.0_3.0_1725788565137.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_ws_extraction_model_27th_mar_2_pipeline_en_5.5.0_3.0_1725788565137.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
+
+pipeline = PretrainedPipeline("burmese_ws_extraction_model_27th_mar_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_ws_extraction_model_27th_mar_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_ws_extraction_model_27th_mar_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/manimaranpa07/my_Ws_extraction_model_27th_mar_2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-camembert_base_adhisetiawan_en.md b/docs/_posts/ahmedlone127/2024-09-08-camembert_base_adhisetiawan_en.md
new file mode 100644
index 00000000000000..e35596dc685741
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-camembert_base_adhisetiawan_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English camembert_base_adhisetiawan CamemBertEmbeddings from adhisetiawan
+author: John Snow Labs
+name: camembert_base_adhisetiawan
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`camembert_base_adhisetiawan` is a English model originally trained by adhisetiawan.
+
+{:.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/camembert_base_adhisetiawan_en_5.5.0_3.0_1725786634081.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/camembert_base_adhisetiawan_en_5.5.0_3.0_1725786634081.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("camembert_base_adhisetiawan","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("camembert_base_adhisetiawan","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|camembert_base_adhisetiawan|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/adhisetiawan/camembert-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-candle_cvss_privileges_en.md b/docs/_posts/ahmedlone127/2024-09-08-candle_cvss_privileges_en.md
new file mode 100644
index 00000000000000..84a4a5cc47e83d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-candle_cvss_privileges_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English candle_cvss_privileges MPNetForSequenceClassification from iashour
+author: John Snow Labs
+name: candle_cvss_privileges
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, mpnet]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`candle_cvss_privileges` is a English model originally trained by iashour.
+
+{:.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/candle_cvss_privileges_en_5.5.0_3.0_1725790341361.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/candle_cvss_privileges_en_5.5.0_3.0_1725790341361.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = MPNetForSequenceClassification.pretrained("candle_cvss_privileges","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = MPNetForSequenceClassification.pretrained("candle_cvss_privileges", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|candle_cvss_privileges|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.5 MB|
+
+## References
+
+https://huggingface.co/iashour/CANDLE_cvss_privileges
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-category_1_delivery_cancellation_distilbert_base_uncased_distilled_squad_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-category_1_delivery_cancellation_distilbert_base_uncased_distilled_squad_v1_pipeline_en.md
new file mode 100644
index 00000000000000..4d7d8e70ba9884
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-category_1_delivery_cancellation_distilbert_base_uncased_distilled_squad_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English category_1_delivery_cancellation_distilbert_base_uncased_distilled_squad_v1_pipeline pipeline DistilBertForSequenceClassification from chuuhtetnaing
+author: John Snow Labs
+name: category_1_delivery_cancellation_distilbert_base_uncased_distilled_squad_v1_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`category_1_delivery_cancellation_distilbert_base_uncased_distilled_squad_v1_pipeline` is a English model originally trained by chuuhtetnaing.
+
+{:.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/category_1_delivery_cancellation_distilbert_base_uncased_distilled_squad_v1_pipeline_en_5.5.0_3.0_1725776756967.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/category_1_delivery_cancellation_distilbert_base_uncased_distilled_squad_v1_pipeline_en_5.5.0_3.0_1725776756967.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
+
+pipeline = PretrainedPipeline("category_1_delivery_cancellation_distilbert_base_uncased_distilled_squad_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("category_1_delivery_cancellation_distilbert_base_uncased_distilled_squad_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|category_1_delivery_cancellation_distilbert_base_uncased_distilled_squad_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.4 MB|
+
+## References
+
+https://huggingface.co/chuuhtetnaing/category-1-delivery-cancellation-distilbert-base-uncased-distilled-squad-v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-chungli_ao_bert_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-chungli_ao_bert_model_pipeline_en.md
new file mode 100644
index 00000000000000..fa43a325a652d8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-chungli_ao_bert_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English chungli_ao_bert_model_pipeline pipeline BertForSequenceClassification from Blue7Bird
+author: John Snow Labs
+name: chungli_ao_bert_model_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chungli_ao_bert_model_pipeline` is a English model originally trained by Blue7Bird.
+
+{:.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/chungli_ao_bert_model_pipeline_en_5.5.0_3.0_1725767889895.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chungli_ao_bert_model_pipeline_en_5.5.0_3.0_1725767889895.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
+
+pipeline = PretrainedPipeline("chungli_ao_bert_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("chungli_ao_bert_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|chungli_ao_bert_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.3 MB|
+
+## References
+
+https://huggingface.co/Blue7Bird/chungli_ao_bert_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-clarify_the_city_bert_first256_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-clarify_the_city_bert_first256_pipeline_en.md
new file mode 100644
index 00000000000000..42cc84c5b4bd7a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-clarify_the_city_bert_first256_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English clarify_the_city_bert_first256_pipeline pipeline BertForSequenceClassification from etadevosyan
+author: John Snow Labs
+name: clarify_the_city_bert_first256_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clarify_the_city_bert_first256_pipeline` is a English model originally trained by etadevosyan.
+
+{:.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/clarify_the_city_bert_first256_pipeline_en_5.5.0_3.0_1725819914165.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clarify_the_city_bert_first256_pipeline_en_5.5.0_3.0_1725819914165.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
+
+pipeline = PretrainedPipeline("clarify_the_city_bert_first256_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clarify_the_city_bert_first256_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clarify_the_city_bert_first256_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|666.5 MB|
+
+## References
+
+https://huggingface.co/etadevosyan/clarify_the_city_bert_First256
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-clas_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-clas_3_pipeline_en.md
new file mode 100644
index 00000000000000..d8b533c2894208
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-clas_3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English clas_3_pipeline pipeline RoBertaForSequenceClassification from BaronSch
+author: John Snow Labs
+name: clas_3_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clas_3_pipeline` is a English model originally trained by BaronSch.
+
+{:.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/clas_3_pipeline_en_5.5.0_3.0_1725821173299.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clas_3_pipeline_en_5.5.0_3.0_1725821173299.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
+
+pipeline = PretrainedPipeline("clas_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("clas_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clas_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.5 MB|
+
+## References
+
+https://huggingface.co/BaronSch/Clas_3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-classification_al_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-classification_al_pipeline_en.md
new file mode 100644
index 00000000000000..857c5800814fcd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-classification_al_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English classification_al_pipeline pipeline MPNetEmbeddings from KikiQi
+author: John Snow Labs
+name: classification_al_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`classification_al_pipeline` is a English model originally trained by KikiQi.
+
+{:.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/classification_al_pipeline_en_5.5.0_3.0_1725815860551.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/classification_al_pipeline_en_5.5.0_3.0_1725815860551.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
+
+pipeline = PretrainedPipeline("classification_al_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("classification_al_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|classification_al_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/KikiQi/classification_AL
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-classification_model_sushant22_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-classification_model_sushant22_pipeline_en.md
new file mode 100644
index 00000000000000..c969c45150fd9e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-classification_model_sushant22_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English classification_model_sushant22_pipeline pipeline DistilBertForSequenceClassification from sushant22
+author: John Snow Labs
+name: classification_model_sushant22_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`classification_model_sushant22_pipeline` is a English model originally trained by sushant22.
+
+{:.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/classification_model_sushant22_pipeline_en_5.5.0_3.0_1725774854632.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/classification_model_sushant22_pipeline_en_5.5.0_3.0_1725774854632.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
+
+pipeline = PretrainedPipeline("classification_model_sushant22_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("classification_model_sushant22_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|classification_model_sushant22_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/sushant22/classification_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-classifier_chapter4_en.md b/docs/_posts/ahmedlone127/2024-09-08-classifier_chapter4_en.md
new file mode 100644
index 00000000000000..06137d3c14bf48
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-classifier_chapter4_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English classifier_chapter4 DistilBertForSequenceClassification from genaibook
+author: John Snow Labs
+name: classifier_chapter4
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`classifier_chapter4` is a English model originally trained by genaibook.
+
+{:.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/classifier_chapter4_en_5.5.0_3.0_1725809065613.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/classifier_chapter4_en_5.5.0_3.0_1725809065613.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("classifier_chapter4","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("classifier_chapter4", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|classifier_chapter4|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/genaibook/classifier-chapter4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-climate_change_belief_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-climate_change_belief_pipeline_en.md
new file mode 100644
index 00000000000000..04572a185ee76d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-climate_change_belief_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English climate_change_belief_pipeline pipeline AlbertForSequenceClassification from robookwus
+author: John Snow Labs
+name: climate_change_belief_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`climate_change_belief_pipeline` is a English model originally trained by robookwus.
+
+{:.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/climate_change_belief_pipeline_en_5.5.0_3.0_1725755928536.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/climate_change_belief_pipeline_en_5.5.0_3.0_1725755928536.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
+
+pipeline = PretrainedPipeline("climate_change_belief_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("climate_change_belief_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|climate_change_belief_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/robookwus/climate-change-belief
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-clinico_xlm_roberta_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-08-clinico_xlm_roberta_finetuned_en.md
new file mode 100644
index 00000000000000..c2cca02c00a301
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-clinico_xlm_roberta_finetuned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English clinico_xlm_roberta_finetuned XlmRoBertaForTokenClassification from joheras
+author: John Snow Labs
+name: clinico_xlm_roberta_finetuned
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clinico_xlm_roberta_finetuned` is a English model originally trained by joheras.
+
+{:.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/clinico_xlm_roberta_finetuned_en_5.5.0_3.0_1725807151521.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clinico_xlm_roberta_finetuned_en_5.5.0_3.0_1725807151521.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("clinico_xlm_roberta_finetuned","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("clinico_xlm_roberta_finetuned", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|clinico_xlm_roberta_finetuned|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|990.1 MB|
+
+## References
+
+https://huggingface.co/joheras/clinico-xlm-roberta-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-conditional_utilitarian_deberta_01_edmundmills_en.md b/docs/_posts/ahmedlone127/2024-09-08-conditional_utilitarian_deberta_01_edmundmills_en.md
new file mode 100644
index 00000000000000..3fe17ff607dbe3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-conditional_utilitarian_deberta_01_edmundmills_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English conditional_utilitarian_deberta_01_edmundmills DeBertaForSequenceClassification from edmundmills
+author: John Snow Labs
+name: conditional_utilitarian_deberta_01_edmundmills
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`conditional_utilitarian_deberta_01_edmundmills` is a English model originally trained by edmundmills.
+
+{:.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/conditional_utilitarian_deberta_01_edmundmills_en_5.5.0_3.0_1725803415233.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/conditional_utilitarian_deberta_01_edmundmills_en_5.5.0_3.0_1725803415233.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("conditional_utilitarian_deberta_01_edmundmills","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("conditional_utilitarian_deberta_01_edmundmills", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|conditional_utilitarian_deberta_01_edmundmills|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/edmundmills/conditional-utilitarian-deberta-01
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-contaminationquestionansweringtry_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-contaminationquestionansweringtry_pipeline_en.md
new file mode 100644
index 00000000000000..5ca720a3a20f50
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-contaminationquestionansweringtry_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English contaminationquestionansweringtry_pipeline pipeline DistilBertForQuestionAnswering from Shushant
+author: John Snow Labs
+name: contaminationquestionansweringtry_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`contaminationquestionansweringtry_pipeline` is a English model originally trained by Shushant.
+
+{:.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/contaminationquestionansweringtry_pipeline_en_5.5.0_3.0_1725798028803.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/contaminationquestionansweringtry_pipeline_en_5.5.0_3.0_1725798028803.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
+
+pipeline = PretrainedPipeline("contaminationquestionansweringtry_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("contaminationquestionansweringtry_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|contaminationquestionansweringtry_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Shushant/ContaminationQuestionAnsweringTry
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-cot_ep3_1234_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-cot_ep3_1234_pipeline_en.md
new file mode 100644
index 00000000000000..b244e181a20c05
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-cot_ep3_1234_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English cot_ep3_1234_pipeline pipeline MPNetEmbeddings from ingeol
+author: John Snow Labs
+name: cot_ep3_1234_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cot_ep3_1234_pipeline` is a English model originally trained by ingeol.
+
+{:.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/cot_ep3_1234_pipeline_en_5.5.0_3.0_1725816140453.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cot_ep3_1234_pipeline_en_5.5.0_3.0_1725816140453.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
+
+pipeline = PretrainedPipeline("cot_ep3_1234_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cot_ep3_1234_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cot_ep3_1234_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/ingeol/cot_ep3_1234
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-cot_ep3_22_en.md b/docs/_posts/ahmedlone127/2024-09-08-cot_ep3_22_en.md
new file mode 100644
index 00000000000000..835b897e3a7d20
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-cot_ep3_22_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English cot_ep3_22 MPNetEmbeddings from ingeol
+author: John Snow Labs
+name: cot_ep3_22
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`cot_ep3_22` is a English model originally trained by ingeol.
+
+{:.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/cot_ep3_22_en_5.5.0_3.0_1725769050762.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cot_ep3_22_en_5.5.0_3.0_1725769050762.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("cot_ep3_22","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("cot_ep3_22","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cot_ep3_22|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/ingeol/cot_ep3_22
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-covid_tweet_sentiment_analysis_roberta_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-covid_tweet_sentiment_analysis_roberta_model_pipeline_en.md
new file mode 100644
index 00000000000000..9fcb4ea5400c67
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-covid_tweet_sentiment_analysis_roberta_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English covid_tweet_sentiment_analysis_roberta_model_pipeline pipeline RoBertaForSequenceClassification from Eva-Gaga
+author: John Snow Labs
+name: covid_tweet_sentiment_analysis_roberta_model_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covid_tweet_sentiment_analysis_roberta_model_pipeline` is a English model originally trained by Eva-Gaga.
+
+{:.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/covid_tweet_sentiment_analysis_roberta_model_pipeline_en_5.5.0_3.0_1725820936185.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covid_tweet_sentiment_analysis_roberta_model_pipeline_en_5.5.0_3.0_1725820936185.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
+
+pipeline = PretrainedPipeline("covid_tweet_sentiment_analysis_roberta_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("covid_tweet_sentiment_analysis_roberta_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|covid_tweet_sentiment_analysis_roberta_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.2 MB|
+
+## References
+
+https://huggingface.co/Eva-Gaga/covid-tweet-sentiment-analysis-roberta_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-cross_all_bs160_allneg_finetuned_webnlg2017_en.md b/docs/_posts/ahmedlone127/2024-09-08-cross_all_bs160_allneg_finetuned_webnlg2017_en.md
new file mode 100644
index 00000000000000..037f75837a6590
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-cross_all_bs160_allneg_finetuned_webnlg2017_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English cross_all_bs160_allneg_finetuned_webnlg2017 MPNetEmbeddings from teven
+author: John Snow Labs
+name: cross_all_bs160_allneg_finetuned_webnlg2017
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`cross_all_bs160_allneg_finetuned_webnlg2017` is a English model originally trained by teven.
+
+{:.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/cross_all_bs160_allneg_finetuned_webnlg2017_en_5.5.0_3.0_1725816073173.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cross_all_bs160_allneg_finetuned_webnlg2017_en_5.5.0_3.0_1725816073173.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("cross_all_bs160_allneg_finetuned_webnlg2017","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("cross_all_bs160_allneg_finetuned_webnlg2017","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cross_all_bs160_allneg_finetuned_webnlg2017|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.3 MB|
+
+## References
+
+https://huggingface.co/teven/cross_all_bs160_allneg_finetuned_WebNLG2017
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-cross_all_bs160_allneg_finetuned_webnlg2017_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-cross_all_bs160_allneg_finetuned_webnlg2017_pipeline_en.md
new file mode 100644
index 00000000000000..9d6f47d1c41093
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-cross_all_bs160_allneg_finetuned_webnlg2017_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English cross_all_bs160_allneg_finetuned_webnlg2017_pipeline pipeline MPNetEmbeddings from teven
+author: John Snow Labs
+name: cross_all_bs160_allneg_finetuned_webnlg2017_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cross_all_bs160_allneg_finetuned_webnlg2017_pipeline` is a English model originally trained by teven.
+
+{:.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/cross_all_bs160_allneg_finetuned_webnlg2017_pipeline_en_5.5.0_3.0_1725816093395.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cross_all_bs160_allneg_finetuned_webnlg2017_pipeline_en_5.5.0_3.0_1725816093395.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
+
+pipeline = PretrainedPipeline("cross_all_bs160_allneg_finetuned_webnlg2017_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cross_all_bs160_allneg_finetuned_webnlg2017_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cross_all_bs160_allneg_finetuned_webnlg2017_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.3 MB|
+
+## References
+
+https://huggingface.co/teven/cross_all_bs160_allneg_finetuned_WebNLG2017
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-cross_all_bs192_hardneg_finetuned_webnlg2020_relevance_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-cross_all_bs192_hardneg_finetuned_webnlg2020_relevance_pipeline_en.md
new file mode 100644
index 00000000000000..ac6b87fab078c6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-cross_all_bs192_hardneg_finetuned_webnlg2020_relevance_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English cross_all_bs192_hardneg_finetuned_webnlg2020_relevance_pipeline pipeline MPNetEmbeddings from teven
+author: John Snow Labs
+name: cross_all_bs192_hardneg_finetuned_webnlg2020_relevance_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cross_all_bs192_hardneg_finetuned_webnlg2020_relevance_pipeline` is a English model originally trained by teven.
+
+{:.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/cross_all_bs192_hardneg_finetuned_webnlg2020_relevance_pipeline_en_5.5.0_3.0_1725769598252.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cross_all_bs192_hardneg_finetuned_webnlg2020_relevance_pipeline_en_5.5.0_3.0_1725769598252.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
+
+pipeline = PretrainedPipeline("cross_all_bs192_hardneg_finetuned_webnlg2020_relevance_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cross_all_bs192_hardneg_finetuned_webnlg2020_relevance_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cross_all_bs192_hardneg_finetuned_webnlg2020_relevance_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.3 MB|
+
+## References
+
+https://huggingface.co/teven/cross_all_bs192_hardneg_finetuned_WebNLG2020_relevance
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-cross_encoder_russian_msmarco_pipeline_ru.md b/docs/_posts/ahmedlone127/2024-09-08-cross_encoder_russian_msmarco_pipeline_ru.md
new file mode 100644
index 00000000000000..cc7987b89463da
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-cross_encoder_russian_msmarco_pipeline_ru.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Russian cross_encoder_russian_msmarco_pipeline pipeline BertForSequenceClassification from DiTy
+author: John Snow Labs
+name: cross_encoder_russian_msmarco_pipeline
+date: 2024-09-08
+tags: [ru, open_source, pipeline, onnx]
+task: Text Classification
+language: ru
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cross_encoder_russian_msmarco_pipeline` is a Russian model originally trained by DiTy.
+
+{:.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/cross_encoder_russian_msmarco_pipeline_ru_5.5.0_3.0_1725802263364.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cross_encoder_russian_msmarco_pipeline_ru_5.5.0_3.0_1725802263364.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
+
+pipeline = PretrainedPipeline("cross_encoder_russian_msmarco_pipeline", lang = "ru")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("cross_encoder_russian_msmarco_pipeline", lang = "ru")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cross_encoder_russian_msmarco_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ru|
+|Size:|666.6 MB|
+
+## References
+
+https://huggingface.co/DiTy/cross-encoder-russian-msmarco
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-cuad_distil_parties_dates_law_08_18_indonesian_question2_en.md b/docs/_posts/ahmedlone127/2024-09-08-cuad_distil_parties_dates_law_08_18_indonesian_question2_en.md
new file mode 100644
index 00000000000000..df7c0df2bd8f52
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-cuad_distil_parties_dates_law_08_18_indonesian_question2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English cuad_distil_parties_dates_law_08_18_indonesian_question2 DistilBertForQuestionAnswering from saraks
+author: John Snow Labs
+name: cuad_distil_parties_dates_law_08_18_indonesian_question2
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cuad_distil_parties_dates_law_08_18_indonesian_question2` is a English model originally trained by saraks.
+
+{:.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/cuad_distil_parties_dates_law_08_18_indonesian_question2_en_5.5.0_3.0_1725798427734.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cuad_distil_parties_dates_law_08_18_indonesian_question2_en_5.5.0_3.0_1725798427734.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("cuad_distil_parties_dates_law_08_18_indonesian_question2","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("cuad_distil_parties_dates_law_08_18_indonesian_question2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cuad_distil_parties_dates_law_08_18_indonesian_question2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/saraks/cuad-distil-parties-dates-law-08-18-id-question2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-customersentiment_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-customersentiment_pipeline_en.md
new file mode 100644
index 00000000000000..5d6503f6ef9cd7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-customersentiment_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English customersentiment_pipeline pipeline DistilBertForSequenceClassification from kearney
+author: John Snow Labs
+name: customersentiment_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`customersentiment_pipeline` is a English model originally trained by kearney.
+
+{:.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/customersentiment_pipeline_en_5.5.0_3.0_1725777163685.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/customersentiment_pipeline_en_5.5.0_3.0_1725777163685.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
+
+pipeline = PretrainedPipeline("customersentiment_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("customersentiment_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|customersentiment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|246.0 MB|
+
+## References
+
+https://huggingface.co/kearney/customersentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-cutiesrun28_05_2020_roberta_base_evidencealignment_en.md b/docs/_posts/ahmedlone127/2024-09-08-cutiesrun28_05_2020_roberta_base_evidencealignment_en.md
new file mode 100644
index 00000000000000..80b698cc8e1c6a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-cutiesrun28_05_2020_roberta_base_evidencealignment_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English cutiesrun28_05_2020_roberta_base_evidencealignment RoBertaForSequenceClassification from yevhenkost
+author: John Snow Labs
+name: cutiesrun28_05_2020_roberta_base_evidencealignment
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cutiesrun28_05_2020_roberta_base_evidencealignment` is a English model originally trained by yevhenkost.
+
+{:.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/cutiesrun28_05_2020_roberta_base_evidencealignment_en_5.5.0_3.0_1725831056036.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cutiesrun28_05_2020_roberta_base_evidencealignment_en_5.5.0_3.0_1725831056036.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("cutiesrun28_05_2020_roberta_base_evidencealignment","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("cutiesrun28_05_2020_roberta_base_evidencealignment", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|cutiesrun28_05_2020_roberta_base_evidencealignment|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|418.0 MB|
+
+## References
+
+https://huggingface.co/yevhenkost/cutiesRun28-05-2020-roberta-base-evidenceAlignment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-darija_englishv2_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-darija_englishv2_1_pipeline_en.md
new file mode 100644
index 00000000000000..74d3091bddec4e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-darija_englishv2_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English darija_englishv2_1_pipeline pipeline MarianTransformer from hananeChab
+author: John Snow Labs
+name: darija_englishv2_1_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`darija_englishv2_1_pipeline` is a English model originally trained by hananeChab.
+
+{:.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/darija_englishv2_1_pipeline_en_5.5.0_3.0_1725765722275.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/darija_englishv2_1_pipeline_en_5.5.0_3.0_1725765722275.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
+
+pipeline = PretrainedPipeline("darija_englishv2_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("darija_englishv2_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|darija_englishv2_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|528.4 MB|
+
+## References
+
+https://huggingface.co/hananeChab/darija_englishV2.1
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-data_20_en.md b/docs/_posts/ahmedlone127/2024-09-08-data_20_en.md
new file mode 100644
index 00000000000000..396288bee7a03e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-data_20_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English data_20 DistilBertForQuestionAnswering from Kajal03
+author: John Snow Labs
+name: data_20
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`data_20` is a English model originally trained by Kajal03.
+
+{:.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/data_20_en_5.5.0_3.0_1725823149918.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/data_20_en_5.5.0_3.0_1725823149918.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("data_20","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("data_20", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|data_20|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Kajal03/Data_20
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-data_20_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-data_20_pipeline_en.md
new file mode 100644
index 00000000000000..b4c46fbc3a2cf6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-data_20_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English data_20_pipeline pipeline DistilBertForQuestionAnswering from Kajal03
+author: John Snow Labs
+name: data_20_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`data_20_pipeline` is a English model originally trained by Kajal03.
+
+{:.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/data_20_pipeline_en_5.5.0_3.0_1725823161661.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/data_20_pipeline_en_5.5.0_3.0_1725823161661.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
+
+pipeline = PretrainedPipeline("data_20_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("data_20_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|data_20_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Kajal03/Data_20
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-dataequity_opus_maltese_german_tagalog_en.md b/docs/_posts/ahmedlone127/2024-09-08-dataequity_opus_maltese_german_tagalog_en.md
new file mode 100644
index 00000000000000..a567a0d7804f9c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-dataequity_opus_maltese_german_tagalog_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dataequity_opus_maltese_german_tagalog MarianTransformer from dataequity
+author: John Snow Labs
+name: dataequity_opus_maltese_german_tagalog
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dataequity_opus_maltese_german_tagalog` is a English model originally trained by dataequity.
+
+{:.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/dataequity_opus_maltese_german_tagalog_en_5.5.0_3.0_1725831958858.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dataequity_opus_maltese_german_tagalog_en_5.5.0_3.0_1725831958858.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("dataequity_opus_maltese_german_tagalog","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("dataequity_opus_maltese_german_tagalog","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dataequity_opus_maltese_german_tagalog|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|515.0 MB|
+
+## References
+
+https://huggingface.co/dataequity/dataequity-opus-mt-de-tl
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-dbbuc_og_en.md b/docs/_posts/ahmedlone127/2024-09-08-dbbuc_og_en.md
new file mode 100644
index 00000000000000..cff0811061ee0b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-dbbuc_og_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dbbuc_og DistilBertForTokenClassification from gabizh
+author: John Snow Labs
+name: dbbuc_og
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dbbuc_og` is a English model originally trained by gabizh.
+
+{:.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/dbbuc_og_en_5.5.0_3.0_1725788631310.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dbbuc_og_en_5.5.0_3.0_1725788631310.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("dbbuc_og","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("dbbuc_og", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dbbuc_og|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/gabizh/dbbuc_OG
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-dbert_model_02_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-dbert_model_02_pipeline_en.md
new file mode 100644
index 00000000000000..e575ebbc8667c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-dbert_model_02_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dbert_model_02_pipeline pipeline DistilBertForTokenClassification from fcfrank10
+author: John Snow Labs
+name: dbert_model_02_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dbert_model_02_pipeline` is a English model originally trained by fcfrank10.
+
+{:.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/dbert_model_02_pipeline_en_5.5.0_3.0_1725788774594.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dbert_model_02_pipeline_en_5.5.0_3.0_1725788774594.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
+
+pipeline = PretrainedPipeline("dbert_model_02_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dbert_model_02_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dbert_model_02_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/fcfrank10/dbert_model_02
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-dbert_model_03_en.md b/docs/_posts/ahmedlone127/2024-09-08-dbert_model_03_en.md
new file mode 100644
index 00000000000000..87e0a52e0037fa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-dbert_model_03_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dbert_model_03 DistilBertForTokenClassification from fcfrank10
+author: John Snow Labs
+name: dbert_model_03
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dbert_model_03` is a English model originally trained by fcfrank10.
+
+{:.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/dbert_model_03_en_5.5.0_3.0_1725827527620.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dbert_model_03_en_5.5.0_3.0_1725827527620.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("dbert_model_03","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("dbert_model_03", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dbert_model_03|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/fcfrank10/dbert_model_03
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-deberta_amazon_reviews_v1_bweb771_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-deberta_amazon_reviews_v1_bweb771_pipeline_en.md
new file mode 100644
index 00000000000000..d52d83ff49bf46
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-deberta_amazon_reviews_v1_bweb771_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_amazon_reviews_v1_bweb771_pipeline pipeline DeBertaForSequenceClassification from bweb771
+author: John Snow Labs
+name: deberta_amazon_reviews_v1_bweb771_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_amazon_reviews_v1_bweb771_pipeline` is a English model originally trained by bweb771.
+
+{:.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/deberta_amazon_reviews_v1_bweb771_pipeline_en_5.5.0_3.0_1725804167715.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_amazon_reviews_v1_bweb771_pipeline_en_5.5.0_3.0_1725804167715.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
+
+pipeline = PretrainedPipeline("deberta_amazon_reviews_v1_bweb771_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_amazon_reviews_v1_bweb771_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_amazon_reviews_v1_bweb771_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|437.4 MB|
+
+## References
+
+https://huggingface.co/bweb771/deberta_amazon_reviews_v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-deberta_base_fine_tune_mnli_half_v1_en.md b/docs/_posts/ahmedlone127/2024-09-08-deberta_base_fine_tune_mnli_half_v1_en.md
new file mode 100644
index 00000000000000..e78e75ecab9bc4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-deberta_base_fine_tune_mnli_half_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_base_fine_tune_mnli_half_v1 DeBertaForSequenceClassification from grace-pro
+author: John Snow Labs
+name: deberta_base_fine_tune_mnli_half_v1
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_base_fine_tune_mnli_half_v1` is a English model originally trained by grace-pro.
+
+{:.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/deberta_base_fine_tune_mnli_half_v1_en_5.5.0_3.0_1725804895873.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_base_fine_tune_mnli_half_v1_en_5.5.0_3.0_1725804895873.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_base_fine_tune_mnli_half_v1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_base_fine_tune_mnli_half_v1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_base_fine_tune_mnli_half_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|643.3 MB|
+
+## References
+
+https://huggingface.co/grace-pro/deberta_base_fine_tune_mnli_half_v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_base_2bit_32rank_0_1dropout_en.md b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_base_2bit_32rank_0_1dropout_en.md
new file mode 100644
index 00000000000000..d0bc8ed2ee28bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_base_2bit_32rank_0_1dropout_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_base_2bit_32rank_0_1dropout DeBertaForSequenceClassification from baohao
+author: John Snow Labs
+name: deberta_v3_base_2bit_32rank_0_1dropout
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_2bit_32rank_0_1dropout` is a English model originally trained by baohao.
+
+{:.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/deberta_v3_base_2bit_32rank_0_1dropout_en_5.5.0_3.0_1725811899420.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_2bit_32rank_0_1dropout_en_5.5.0_3.0_1725811899420.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_base_2bit_32rank_0_1dropout","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_2bit_32rank_0_1dropout", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_2bit_32rank_0_1dropout|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|267.6 MB|
+
+## References
+
+https://huggingface.co/baohao/deberta-v3-base-2bit-32rank-0.1dropout
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_base_2bit_32rank_0_1dropout_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_base_2bit_32rank_0_1dropout_pipeline_en.md
new file mode 100644
index 00000000000000..702c89019b62c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_base_2bit_32rank_0_1dropout_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_base_2bit_32rank_0_1dropout_pipeline pipeline DeBertaForSequenceClassification from baohao
+author: John Snow Labs
+name: deberta_v3_base_2bit_32rank_0_1dropout_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_2bit_32rank_0_1dropout_pipeline` is a English model originally trained by baohao.
+
+{:.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/deberta_v3_base_2bit_32rank_0_1dropout_pipeline_en_5.5.0_3.0_1725811988455.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_2bit_32rank_0_1dropout_pipeline_en_5.5.0_3.0_1725811988455.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
+
+pipeline = PretrainedPipeline("deberta_v3_base_2bit_32rank_0_1dropout_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_base_2bit_32rank_0_1dropout_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_2bit_32rank_0_1dropout_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|267.6 MB|
+
+## References
+
+https://huggingface.co/baohao/deberta-v3-base-2bit-32rank-0.1dropout
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_base_finetuned_emotion_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_base_finetuned_emotion_pipeline_en.md
new file mode 100644
index 00000000000000..825a939f961a88
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_base_finetuned_emotion_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_base_finetuned_emotion_pipeline pipeline DeBertaForSequenceClassification from vroomhf
+author: John Snow Labs
+name: deberta_v3_base_finetuned_emotion_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_finetuned_emotion_pipeline` is a English model originally trained by vroomhf.
+
+{:.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/deberta_v3_base_finetuned_emotion_pipeline_en_5.5.0_3.0_1725803360506.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_finetuned_emotion_pipeline_en_5.5.0_3.0_1725803360506.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
+
+pipeline = PretrainedPipeline("deberta_v3_base_finetuned_emotion_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_base_finetuned_emotion_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_finetuned_emotion_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|586.5 MB|
+
+## References
+
+https://huggingface.co/vroomhf/deberta-v3-base-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_base_market_en.md b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_base_market_en.md
new file mode 100644
index 00000000000000..fcd7f467f9ace3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_base_market_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_base_market DeBertaForSequenceClassification from Isotonic
+author: John Snow Labs
+name: deberta_v3_base_market
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_market` is a English model originally trained by Isotonic.
+
+{:.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/deberta_v3_base_market_en_5.5.0_3.0_1725802971489.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_market_en_5.5.0_3.0_1725802971489.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_base_market","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_market", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_market|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|578.3 MB|
+
+## References
+
+https://huggingface.co/Isotonic/deberta-v3-base-market
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_base_market_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_base_market_pipeline_en.md
new file mode 100644
index 00000000000000..018d1c6d925e94
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_base_market_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_base_market_pipeline pipeline DeBertaForSequenceClassification from Isotonic
+author: John Snow Labs
+name: deberta_v3_base_market_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_market_pipeline` is a English model originally trained by Isotonic.
+
+{:.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/deberta_v3_base_market_pipeline_en_5.5.0_3.0_1725803017878.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_market_pipeline_en_5.5.0_3.0_1725803017878.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
+
+pipeline = PretrainedPipeline("deberta_v3_base_market_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_base_market_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_market_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|578.3 MB|
+
+## References
+
+https://huggingface.co/Isotonic/deberta-v3-base-market
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_base_mnli_10_19_v0_en.md b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_base_mnli_10_19_v0_en.md
new file mode 100644
index 00000000000000..ff7ca1c219981c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_base_mnli_10_19_v0_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_base_mnli_10_19_v0 DeBertaForSequenceClassification from mariolinml
+author: John Snow Labs
+name: deberta_v3_base_mnli_10_19_v0
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_mnli_10_19_v0` is a English model originally trained by mariolinml.
+
+{:.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/deberta_v3_base_mnli_10_19_v0_en_5.5.0_3.0_1725803576011.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_mnli_10_19_v0_en_5.5.0_3.0_1725803576011.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_base_mnli_10_19_v0","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_mnli_10_19_v0", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_mnli_10_19_v0|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|636.4 MB|
+
+## References
+
+https://huggingface.co/mariolinml/deberta-v3-base_MNLI_10_19_v0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_base_mnli_10_19_v0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_base_mnli_10_19_v0_pipeline_en.md
new file mode 100644
index 00000000000000..d08cfa53f22670
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_base_mnli_10_19_v0_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_base_mnli_10_19_v0_pipeline pipeline DeBertaForSequenceClassification from mariolinml
+author: John Snow Labs
+name: deberta_v3_base_mnli_10_19_v0_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_mnli_10_19_v0_pipeline` is a English model originally trained by mariolinml.
+
+{:.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/deberta_v3_base_mnli_10_19_v0_pipeline_en_5.5.0_3.0_1725803627410.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_mnli_10_19_v0_pipeline_en_5.5.0_3.0_1725803627410.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
+
+pipeline = PretrainedPipeline("deberta_v3_base_mnli_10_19_v0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_base_mnli_10_19_v0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_mnli_10_19_v0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|636.5 MB|
+
+## References
+
+https://huggingface.co/mariolinml/deberta-v3-base_MNLI_10_19_v0
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_base_tasksource_sentiment_en.md b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_base_tasksource_sentiment_en.md
new file mode 100644
index 00000000000000..51038f64a722f2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_base_tasksource_sentiment_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_base_tasksource_sentiment DeBertaForSequenceClassification from sileod
+author: John Snow Labs
+name: deberta_v3_base_tasksource_sentiment
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_tasksource_sentiment` is a English model originally trained by sileod.
+
+{:.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/deberta_v3_base_tasksource_sentiment_en_5.5.0_3.0_1725802911025.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_tasksource_sentiment_en_5.5.0_3.0_1725802911025.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_base_tasksource_sentiment","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_tasksource_sentiment", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_tasksource_sentiment|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|688.9 MB|
+
+## References
+
+https://huggingface.co/sileod/deberta-v3-base-tasksource-sentiment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large__sst2__train_8_3_en.md b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large__sst2__train_8_3_en.md
new file mode 100644
index 00000000000000..02aa249bf67a58
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large__sst2__train_8_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_large__sst2__train_8_3 DeBertaForSequenceClassification from SetFit
+author: John Snow Labs
+name: deberta_v3_large__sst2__train_8_3
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large__sst2__train_8_3` is a English model originally trained by SetFit.
+
+{:.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/deberta_v3_large__sst2__train_8_3_en_5.5.0_3.0_1725804400925.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_8_3_en_5.5.0_3.0_1725804400925.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_large__sst2__train_8_3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large__sst2__train_8_3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large__sst2__train_8_3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/SetFit/deberta-v3-large__sst2__train-8-3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large__sst2__train_8_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large__sst2__train_8_3_pipeline_en.md
new file mode 100644
index 00000000000000..d916dcda7c3ac6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large__sst2__train_8_3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_large__sst2__train_8_3_pipeline pipeline DeBertaForSequenceClassification from SetFit
+author: John Snow Labs
+name: deberta_v3_large__sst2__train_8_3_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large__sst2__train_8_3_pipeline` is a English model originally trained by SetFit.
+
+{:.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/deberta_v3_large__sst2__train_8_3_pipeline_en_5.5.0_3.0_1725804525566.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_8_3_pipeline_en_5.5.0_3.0_1725804525566.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
+
+pipeline = PretrainedPipeline("deberta_v3_large__sst2__train_8_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large__sst2__train_8_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large__sst2__train_8_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/SetFit/deberta-v3-large__sst2__train-8-3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_dapt_tapt_scientific_papers_pubmed_finetuned_dagpap22_en.md b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_dapt_tapt_scientific_papers_pubmed_finetuned_dagpap22_en.md
new file mode 100644
index 00000000000000..caa9abf06da09a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_dapt_tapt_scientific_papers_pubmed_finetuned_dagpap22_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_large_dapt_tapt_scientific_papers_pubmed_finetuned_dagpap22 DeBertaForSequenceClassification from domenicrosati
+author: John Snow Labs
+name: deberta_v3_large_dapt_tapt_scientific_papers_pubmed_finetuned_dagpap22
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_dapt_tapt_scientific_papers_pubmed_finetuned_dagpap22` is a English model originally trained by domenicrosati.
+
+{:.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/deberta_v3_large_dapt_tapt_scientific_papers_pubmed_finetuned_dagpap22_en_5.5.0_3.0_1725804606090.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_dapt_tapt_scientific_papers_pubmed_finetuned_dagpap22_en_5.5.0_3.0_1725804606090.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_large_dapt_tapt_scientific_papers_pubmed_finetuned_dagpap22","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_dapt_tapt_scientific_papers_pubmed_finetuned_dagpap22", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_dapt_tapt_scientific_papers_pubmed_finetuned_dagpap22|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/domenicrosati/deberta-v3-large-dapt-tapt-scientific-papers-pubmed-finetuned-DAGPap22
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_finetuned_dagpap22_synthetic_all_overfit_en.md b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_finetuned_dagpap22_synthetic_all_overfit_en.md
new file mode 100644
index 00000000000000..b7fb3b68a13937
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_finetuned_dagpap22_synthetic_all_overfit_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_large_finetuned_dagpap22_synthetic_all_overfit DeBertaForSequenceClassification from domenicrosati
+author: John Snow Labs
+name: deberta_v3_large_finetuned_dagpap22_synthetic_all_overfit
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_finetuned_dagpap22_synthetic_all_overfit` is a English model originally trained by domenicrosati.
+
+{:.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/deberta_v3_large_finetuned_dagpap22_synthetic_all_overfit_en_5.5.0_3.0_1725803100107.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_finetuned_dagpap22_synthetic_all_overfit_en_5.5.0_3.0_1725803100107.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_large_finetuned_dagpap22_synthetic_all_overfit","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_finetuned_dagpap22_synthetic_all_overfit", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_finetuned_dagpap22_synthetic_all_overfit|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/domenicrosati/deberta-v3-large-finetuned-DAGPap22-synthetic-all-overfit
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_imdb_v0_2_en.md b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_imdb_v0_2_en.md
new file mode 100644
index 00000000000000..624f2a77209cbe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_imdb_v0_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_large_imdb_v0_2 DeBertaForSequenceClassification from dfurman
+author: John Snow Labs
+name: deberta_v3_large_imdb_v0_2
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_imdb_v0_2` is a English model originally trained by dfurman.
+
+{:.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/deberta_v3_large_imdb_v0_2_en_5.5.0_3.0_1725812594479.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_imdb_v0_2_en_5.5.0_3.0_1725812594479.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_large_imdb_v0_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_imdb_v0_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_imdb_v0_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/dfurman/deberta-v3-large-imdb-v0.2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_llmmdlprefold_rank_20_09_2023_0_en.md b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_llmmdlprefold_rank_20_09_2023_0_en.md
new file mode 100644
index 00000000000000..0ad6336e4900b3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_llmmdlprefold_rank_20_09_2023_0_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_large_llmmdlprefold_rank_20_09_2023_0 DeBertaForSequenceClassification from nagupv
+author: John Snow Labs
+name: deberta_v3_large_llmmdlprefold_rank_20_09_2023_0
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_llmmdlprefold_rank_20_09_2023_0` is a English model originally trained by nagupv.
+
+{:.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/deberta_v3_large_llmmdlprefold_rank_20_09_2023_0_en_5.5.0_3.0_1725804842763.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_llmmdlprefold_rank_20_09_2023_0_en_5.5.0_3.0_1725804842763.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_large_llmmdlprefold_rank_20_09_2023_0","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_llmmdlprefold_rank_20_09_2023_0", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_llmmdlprefold_rank_20_09_2023_0|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/nagupv/deberta-v3-large_LLMMDLPREFOLD_RANK_20_09_2023_0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_model_edit_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_model_edit_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..fa7cbf78e3e885
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_model_edit_classifier_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_large_model_edit_classifier_pipeline pipeline DeBertaForSequenceClassification from domenicrosati
+author: John Snow Labs
+name: deberta_v3_large_model_edit_classifier_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_model_edit_classifier_pipeline` is a English model originally trained by domenicrosati.
+
+{:.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/deberta_v3_large_model_edit_classifier_pipeline_en_5.5.0_3.0_1725803832741.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_model_edit_classifier_pipeline_en_5.5.0_3.0_1725803832741.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
+
+pipeline = PretrainedPipeline("deberta_v3_large_model_edit_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large_model_edit_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_model_edit_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/domenicrosati/deberta-v3-large-model-edit-classifier
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_rationale_tonga_tonga_islands_score_en.md b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_rationale_tonga_tonga_islands_score_en.md
new file mode 100644
index 00000000000000..ab34f9ea978bae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_rationale_tonga_tonga_islands_score_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_large_rationale_tonga_tonga_islands_score DeBertaForSequenceClassification from jiazhengli
+author: John Snow Labs
+name: deberta_v3_large_rationale_tonga_tonga_islands_score
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_rationale_tonga_tonga_islands_score` is a English model originally trained by jiazhengli.
+
+{:.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/deberta_v3_large_rationale_tonga_tonga_islands_score_en_5.5.0_3.0_1725804840244.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_rationale_tonga_tonga_islands_score_en_5.5.0_3.0_1725804840244.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_large_rationale_tonga_tonga_islands_score","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_rationale_tonga_tonga_islands_score", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_rationale_tonga_tonga_islands_score|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/jiazhengli/deberta-v3-large-Rationale-to-Score
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_survey_cross_passage_consistency_rater_half_en.md b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_survey_cross_passage_consistency_rater_half_en.md
new file mode 100644
index 00000000000000..989dbd9921addb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_survey_cross_passage_consistency_rater_half_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_large_survey_cross_passage_consistency_rater_half DeBertaForSequenceClassification from domenicrosati
+author: John Snow Labs
+name: deberta_v3_large_survey_cross_passage_consistency_rater_half
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_survey_cross_passage_consistency_rater_half` is a English model originally trained by domenicrosati.
+
+{:.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/deberta_v3_large_survey_cross_passage_consistency_rater_half_en_5.5.0_3.0_1725810848521.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_cross_passage_consistency_rater_half_en_5.5.0_3.0_1725810848521.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_large_survey_cross_passage_consistency_rater_half","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_survey_cross_passage_consistency_rater_half", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_survey_cross_passage_consistency_rater_half|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/domenicrosati/deberta-v3-large-survey-cross_passage_consistency-rater-half
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_survey_cross_passage_consistency_rater_half_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_survey_cross_passage_consistency_rater_half_pipeline_en.md
new file mode 100644
index 00000000000000..c54419b119aff3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_survey_cross_passage_consistency_rater_half_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_large_survey_cross_passage_consistency_rater_half_pipeline pipeline DeBertaForSequenceClassification from domenicrosati
+author: John Snow Labs
+name: deberta_v3_large_survey_cross_passage_consistency_rater_half_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_survey_cross_passage_consistency_rater_half_pipeline` is a English model originally trained by domenicrosati.
+
+{:.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/deberta_v3_large_survey_cross_passage_consistency_rater_half_pipeline_en_5.5.0_3.0_1725810951618.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_cross_passage_consistency_rater_half_pipeline_en_5.5.0_3.0_1725810951618.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
+
+pipeline = PretrainedPipeline("deberta_v3_large_survey_cross_passage_consistency_rater_half_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large_survey_cross_passage_consistency_rater_half_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_survey_cross_passage_consistency_rater_half_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/domenicrosati/deberta-v3-large-survey-cross_passage_consistency-rater-half
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_survey_main_passage_consistency_rater_all_gpt4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_survey_main_passage_consistency_rater_all_gpt4_pipeline_en.md
new file mode 100644
index 00000000000000..9078d7c8bf7220
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_survey_main_passage_consistency_rater_all_gpt4_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_large_survey_main_passage_consistency_rater_all_gpt4_pipeline pipeline DeBertaForSequenceClassification from domenicrosati
+author: John Snow Labs
+name: deberta_v3_large_survey_main_passage_consistency_rater_all_gpt4_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_survey_main_passage_consistency_rater_all_gpt4_pipeline` is a English model originally trained by domenicrosati.
+
+{:.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/deberta_v3_large_survey_main_passage_consistency_rater_all_gpt4_pipeline_en_5.5.0_3.0_1725812816733.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_main_passage_consistency_rater_all_gpt4_pipeline_en_5.5.0_3.0_1725812816733.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
+
+pipeline = PretrainedPipeline("deberta_v3_large_survey_main_passage_consistency_rater_all_gpt4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large_survey_main_passage_consistency_rater_all_gpt4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_survey_main_passage_consistency_rater_all_gpt4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/domenicrosati/deberta-v3-large-survey-main_passage_consistency-rater-all-gpt4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_survey_topicality_rater_gpt4_en.md b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_survey_topicality_rater_gpt4_en.md
new file mode 100644
index 00000000000000..c7d21178269ffa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_survey_topicality_rater_gpt4_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_large_survey_topicality_rater_gpt4 DeBertaForSequenceClassification from domenicrosati
+author: John Snow Labs
+name: deberta_v3_large_survey_topicality_rater_gpt4
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_survey_topicality_rater_gpt4` is a English model originally trained by domenicrosati.
+
+{:.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/deberta_v3_large_survey_topicality_rater_gpt4_en_5.5.0_3.0_1725811480324.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_topicality_rater_gpt4_en_5.5.0_3.0_1725811480324.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_large_survey_topicality_rater_gpt4","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_survey_topicality_rater_gpt4", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_survey_topicality_rater_gpt4|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/domenicrosati/deberta-v3-large-survey-topicality-rater-gpt4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_survey_topicality_rater_half_gpt4_en.md b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_survey_topicality_rater_half_gpt4_en.md
new file mode 100644
index 00000000000000..c8e0721cf9455d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_large_survey_topicality_rater_half_gpt4_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_large_survey_topicality_rater_half_gpt4 DeBertaForSequenceClassification from domenicrosati
+author: John Snow Labs
+name: deberta_v3_large_survey_topicality_rater_half_gpt4
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_survey_topicality_rater_half_gpt4` is a English model originally trained by domenicrosati.
+
+{:.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/deberta_v3_large_survey_topicality_rater_half_gpt4_en_5.5.0_3.0_1725812094534.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_topicality_rater_half_gpt4_en_5.5.0_3.0_1725812094534.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_large_survey_topicality_rater_half_gpt4","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_survey_topicality_rater_half_gpt4", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_survey_topicality_rater_half_gpt4|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/domenicrosati/deberta-v3-large-survey-topicality-rater-half-gpt4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_small_chaiblend_en.md b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_small_chaiblend_en.md
new file mode 100644
index 00000000000000..1bba8fad433d55
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_small_chaiblend_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_small_chaiblend DeBertaForSequenceClassification from chargoddard
+author: John Snow Labs
+name: deberta_v3_small_chaiblend
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_chaiblend` is a English model originally trained by chargoddard.
+
+{:.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/deberta_v3_small_chaiblend_en_5.5.0_3.0_1725803890186.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_chaiblend_en_5.5.0_3.0_1725803890186.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_small_chaiblend","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_small_chaiblend", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_small_chaiblend|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|271.6 MB|
+
+## References
+
+https://huggingface.co/chargoddard/deberta-v3-small-chaiblend
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_small_chaiblend_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_small_chaiblend_pipeline_en.md
new file mode 100644
index 00000000000000..d6d3c01b8cf93e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_small_chaiblend_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_small_chaiblend_pipeline pipeline DeBertaForSequenceClassification from chargoddard
+author: John Snow Labs
+name: deberta_v3_small_chaiblend_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_chaiblend_pipeline` is a English model originally trained by chargoddard.
+
+{:.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/deberta_v3_small_chaiblend_pipeline_en_5.5.0_3.0_1725803981640.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_chaiblend_pipeline_en_5.5.0_3.0_1725803981640.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
+
+pipeline = PretrainedPipeline("deberta_v3_small_chaiblend_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_small_chaiblend_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_small_chaiblend_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|271.6 MB|
+
+## References
+
+https://huggingface.co/chargoddard/deberta-v3-small-chaiblend
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_xsmall_survey_nepal_bhasa_fact_main_passage_rater_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_xsmall_survey_nepal_bhasa_fact_main_passage_rater_pipeline_en.md
new file mode 100644
index 00000000000000..3c6291f7a6e48b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_xsmall_survey_nepal_bhasa_fact_main_passage_rater_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_xsmall_survey_nepal_bhasa_fact_main_passage_rater_pipeline pipeline DeBertaForSequenceClassification from domenicrosati
+author: John Snow Labs
+name: deberta_v3_xsmall_survey_nepal_bhasa_fact_main_passage_rater_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_survey_nepal_bhasa_fact_main_passage_rater_pipeline` is a English model originally trained by domenicrosati.
+
+{:.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/deberta_v3_xsmall_survey_nepal_bhasa_fact_main_passage_rater_pipeline_en_5.5.0_3.0_1725804367064.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_survey_nepal_bhasa_fact_main_passage_rater_pipeline_en_5.5.0_3.0_1725804367064.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
+
+pipeline = PretrainedPipeline("deberta_v3_xsmall_survey_nepal_bhasa_fact_main_passage_rater_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_xsmall_survey_nepal_bhasa_fact_main_passage_rater_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_xsmall_survey_nepal_bhasa_fact_main_passage_rater_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|224.9 MB|
+
+## References
+
+https://huggingface.co/domenicrosati/deberta-v3-xsmall-survey-new_fact_main_passage-rater
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_xsmall_survey_rater_sample_1_en.md b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_xsmall_survey_rater_sample_1_en.md
new file mode 100644
index 00000000000000..c941fa0b1c0f95
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_xsmall_survey_rater_sample_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_xsmall_survey_rater_sample_1 DeBertaForSequenceClassification from domenicrosati
+author: John Snow Labs
+name: deberta_v3_xsmall_survey_rater_sample_1
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_survey_rater_sample_1` is a English model originally trained by domenicrosati.
+
+{:.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/deberta_v3_xsmall_survey_rater_sample_1_en_5.5.0_3.0_1725810706856.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_survey_rater_sample_1_en_5.5.0_3.0_1725810706856.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_xsmall_survey_rater_sample_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_xsmall_survey_rater_sample_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_xsmall_survey_rater_sample_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|226.8 MB|
+
+## References
+
+https://huggingface.co/domenicrosati/deberta-v3-xsmall-survey-rater-sample-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_xsmall_survey_rater_sample_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_xsmall_survey_rater_sample_1_pipeline_en.md
new file mode 100644
index 00000000000000..aad95ba26b7d1d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-deberta_v3_xsmall_survey_rater_sample_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_xsmall_survey_rater_sample_1_pipeline pipeline DeBertaForSequenceClassification from domenicrosati
+author: John Snow Labs
+name: deberta_v3_xsmall_survey_rater_sample_1_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_survey_rater_sample_1_pipeline` is a English model originally trained by domenicrosati.
+
+{:.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/deberta_v3_xsmall_survey_rater_sample_1_pipeline_en_5.5.0_3.0_1725810723527.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_survey_rater_sample_1_pipeline_en_5.5.0_3.0_1725810723527.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
+
+pipeline = PretrainedPipeline("deberta_v3_xsmall_survey_rater_sample_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_xsmall_survey_rater_sample_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_xsmall_survey_rater_sample_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|226.8 MB|
+
+## References
+
+https://huggingface.co/domenicrosati/deberta-v3-xsmall-survey-rater-sample-1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-depression_detection_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-depression_detection_model_pipeline_en.md
new file mode 100644
index 00000000000000..399268119c025c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-depression_detection_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English depression_detection_model_pipeline pipeline DistilBertForSequenceClassification from thePixel42
+author: John Snow Labs
+name: depression_detection_model_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`depression_detection_model_pipeline` is a English model originally trained by thePixel42.
+
+{:.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/depression_detection_model_pipeline_en_5.5.0_3.0_1725777114119.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/depression_detection_model_pipeline_en_5.5.0_3.0_1725777114119.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
+
+pipeline = PretrainedPipeline("depression_detection_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("depression_detection_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|depression_detection_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/thePixel42/depression_detection_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-dialecttransliterator_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-dialecttransliterator_pipeline_en.md
new file mode 100644
index 00000000000000..d22e2e291f12cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-dialecttransliterator_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dialecttransliterator_pipeline pipeline MarianTransformer from guymorlan
+author: John Snow Labs
+name: dialecttransliterator_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dialecttransliterator_pipeline` is a English model originally trained by guymorlan.
+
+{:.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/dialecttransliterator_pipeline_en_5.5.0_3.0_1725795052480.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dialecttransliterator_pipeline_en_5.5.0_3.0_1725795052480.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
+
+pipeline = PretrainedPipeline("dialecttransliterator_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dialecttransliterator_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dialecttransliterator_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|528.0 MB|
+
+## References
+
+https://huggingface.co/guymorlan/DialectTransliterator
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-did_the_doctor_say_that_the_medical_report_would_belarusian_in_a_specific_time_bert_last128_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-did_the_doctor_say_that_the_medical_report_would_belarusian_in_a_specific_time_bert_last128_pipeline_en.md
new file mode 100644
index 00000000000000..9f99556bf9eafa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-did_the_doctor_say_that_the_medical_report_would_belarusian_in_a_specific_time_bert_last128_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English did_the_doctor_say_that_the_medical_report_would_belarusian_in_a_specific_time_bert_last128_pipeline pipeline BertForSequenceClassification from etadevosyan
+author: John Snow Labs
+name: did_the_doctor_say_that_the_medical_report_would_belarusian_in_a_specific_time_bert_last128_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`did_the_doctor_say_that_the_medical_report_would_belarusian_in_a_specific_time_bert_last128_pipeline` is a English model originally trained by etadevosyan.
+
+{:.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/did_the_doctor_say_that_the_medical_report_would_belarusian_in_a_specific_time_bert_last128_pipeline_en_5.5.0_3.0_1725818988912.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/did_the_doctor_say_that_the_medical_report_would_belarusian_in_a_specific_time_bert_last128_pipeline_en_5.5.0_3.0_1725818988912.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
+
+pipeline = PretrainedPipeline("did_the_doctor_say_that_the_medical_report_would_belarusian_in_a_specific_time_bert_last128_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("did_the_doctor_say_that_the_medical_report_would_belarusian_in_a_specific_time_bert_last128_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|did_the_doctor_say_that_the_medical_report_would_belarusian_in_a_specific_time_bert_last128_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|666.5 MB|
+
+## References
+
+https://huggingface.co/etadevosyan/did_the_doctor_say_that_the_medical_report_would_be_in_a_specific_time_bert_Last128
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-did_you_take_drugs_bert_last512_en.md b/docs/_posts/ahmedlone127/2024-09-08-did_you_take_drugs_bert_last512_en.md
new file mode 100644
index 00000000000000..e380421a287713
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-did_you_take_drugs_bert_last512_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English did_you_take_drugs_bert_last512 BertForSequenceClassification from etadevosyan
+author: John Snow Labs
+name: did_you_take_drugs_bert_last512
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`did_you_take_drugs_bert_last512` is a English model originally trained by etadevosyan.
+
+{:.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/did_you_take_drugs_bert_last512_en_5.5.0_3.0_1725819312432.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/did_you_take_drugs_bert_last512_en_5.5.0_3.0_1725819312432.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("did_you_take_drugs_bert_last512","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("did_you_take_drugs_bert_last512", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|did_you_take_drugs_bert_last512|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|666.5 MB|
+
+## References
+
+https://huggingface.co/etadevosyan/did_you_take_drugs_bert_Last512
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-did_you_take_drugs_bert_last512_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-did_you_take_drugs_bert_last512_pipeline_en.md
new file mode 100644
index 00000000000000..182bc11f7b25a8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-did_you_take_drugs_bert_last512_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English did_you_take_drugs_bert_last512_pipeline pipeline BertForSequenceClassification from etadevosyan
+author: John Snow Labs
+name: did_you_take_drugs_bert_last512_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`did_you_take_drugs_bert_last512_pipeline` is a English model originally trained by etadevosyan.
+
+{:.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/did_you_take_drugs_bert_last512_pipeline_en_5.5.0_3.0_1725819350620.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/did_you_take_drugs_bert_last512_pipeline_en_5.5.0_3.0_1725819350620.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
+
+pipeline = PretrainedPipeline("did_you_take_drugs_bert_last512_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("did_you_take_drugs_bert_last512_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|did_you_take_drugs_bert_last512_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|666.5 MB|
+
+## References
+
+https://huggingface.co/etadevosyan/did_you_take_drugs_bert_Last512
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distelbert_en.md b/docs/_posts/ahmedlone127/2024-09-08-distelbert_en.md
new file mode 100644
index 00000000000000..e37529046ba0cd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distelbert_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distelbert DistilBertForQuestionAnswering from juman48
+author: John Snow Labs
+name: distelbert
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distelbert` is a English model originally trained by juman48.
+
+{:.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/distelbert_en_5.5.0_3.0_1725823091532.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distelbert_en_5.5.0_3.0_1725823091532.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distelbert","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distelbert", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distelbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/juman48/Distelbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distil_bert_fintuned_issues_cfpb_complaints_en.md b/docs/_posts/ahmedlone127/2024-09-08-distil_bert_fintuned_issues_cfpb_complaints_en.md
new file mode 100644
index 00000000000000..c4e1335747440f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distil_bert_fintuned_issues_cfpb_complaints_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distil_bert_fintuned_issues_cfpb_complaints DistilBertForSequenceClassification from Mahesh9
+author: John Snow Labs
+name: distil_bert_fintuned_issues_cfpb_complaints
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distil_bert_fintuned_issues_cfpb_complaints` is a English model originally trained by Mahesh9.
+
+{:.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/distil_bert_fintuned_issues_cfpb_complaints_en_5.5.0_3.0_1725809208808.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distil_bert_fintuned_issues_cfpb_complaints_en_5.5.0_3.0_1725809208808.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distil_bert_fintuned_issues_cfpb_complaints","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distil_bert_fintuned_issues_cfpb_complaints", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distil_bert_fintuned_issues_cfpb_complaints|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Mahesh9/distil-bert-fintuned-issues-cfpb-complaints
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distil_rubert_contacts_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distil_rubert_contacts_pipeline_en.md
new file mode 100644
index 00000000000000..ed091955808a04
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distil_rubert_contacts_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distil_rubert_contacts_pipeline pipeline BertForSequenceClassification from zkv
+author: John Snow Labs
+name: distil_rubert_contacts_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distil_rubert_contacts_pipeline` is a English model originally trained by zkv.
+
+{:.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/distil_rubert_contacts_pipeline_en_5.5.0_3.0_1725819775673.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distil_rubert_contacts_pipeline_en_5.5.0_3.0_1725819775673.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
+
+pipeline = PretrainedPipeline("distil_rubert_contacts_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distil_rubert_contacts_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distil_rubert_contacts_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|109.5 MB|
+
+## References
+
+https://huggingface.co/zkv/distil_rubert_contacts
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_cased_distilled_squad_bnb_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_cased_distilled_squad_bnb_pipeline_en.md
new file mode 100644
index 00000000000000..d2ffff5552086e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_cased_distilled_squad_bnb_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_cased_distilled_squad_bnb_pipeline pipeline DistilBertForQuestionAnswering from dmedhi
+author: John Snow Labs
+name: distilbert_base_cased_distilled_squad_bnb_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_cased_distilled_squad_bnb_pipeline` is a English model originally trained by dmedhi.
+
+{:.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/distilbert_base_cased_distilled_squad_bnb_pipeline_en_5.5.0_3.0_1725798513788.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_cased_distilled_squad_bnb_pipeline_en_5.5.0_3.0_1725798513788.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
+
+pipeline = PretrainedPipeline("distilbert_base_cased_distilled_squad_bnb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_cased_distilled_squad_bnb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_cased_distilled_squad_bnb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|116.6 MB|
+
+## References
+
+https://huggingface.co/dmedhi/distilbert-base-cased-distilled-squad-bnb
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_cased_finetuned_squadbn_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_cased_finetuned_squadbn_en.md
new file mode 100644
index 00000000000000..668d714a73351a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_cased_finetuned_squadbn_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_base_cased_finetuned_squadbn DistilBertForQuestionAnswering from AsifAbrar6
+author: John Snow Labs
+name: distilbert_base_cased_finetuned_squadbn
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_cased_finetuned_squadbn` is a English model originally trained by AsifAbrar6.
+
+{:.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/distilbert_base_cased_finetuned_squadbn_en_5.5.0_3.0_1725798344249.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_cased_finetuned_squadbn_en_5.5.0_3.0_1725798344249.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_cased_finetuned_squadbn","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_cased_finetuned_squadbn", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_cased_finetuned_squadbn|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/AsifAbrar6/distilbert-base-cased-finetuned-squadBN
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_multilingual_cased_finetuned_english_german_spanish_xx.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_multilingual_cased_finetuned_english_german_spanish_xx.md
new file mode 100644
index 00000000000000..7f61c4b739229c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_multilingual_cased_finetuned_english_german_spanish_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual distilbert_base_multilingual_cased_finetuned_english_german_spanish DistilBertEmbeddings from lusxvr
+author: John Snow Labs
+name: distilbert_base_multilingual_cased_finetuned_english_german_spanish
+date: 2024-09-08
+tags: [xx, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_multilingual_cased_finetuned_english_german_spanish` is a Multilingual model originally trained by lusxvr.
+
+{:.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/distilbert_base_multilingual_cased_finetuned_english_german_spanish_xx_5.5.0_3.0_1725775912092.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_finetuned_english_german_spanish_xx_5.5.0_3.0_1725775912092.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_multilingual_cased_finetuned_english_german_spanish","xx") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_multilingual_cased_finetuned_english_german_spanish","xx") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_multilingual_cased_finetuned_english_german_spanish|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|xx|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/lusxvr/distilbert-base-multilingual-cased-finetuned-en_de_es
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_spanish_uncased_2023_11_13_18_01_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_spanish_uncased_2023_11_13_18_01_en.md
new file mode 100644
index 00000000000000..ce3148b77e7b05
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_spanish_uncased_2023_11_13_18_01_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_spanish_uncased_2023_11_13_18_01 DistilBertEmbeddings from Santp98
+author: John Snow Labs
+name: distilbert_base_spanish_uncased_2023_11_13_18_01
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_spanish_uncased_2023_11_13_18_01` is a English model originally trained by Santp98.
+
+{:.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/distilbert_base_spanish_uncased_2023_11_13_18_01_en_5.5.0_3.0_1725828924227.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_spanish_uncased_2023_11_13_18_01_en_5.5.0_3.0_1725828924227.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_spanish_uncased_2023_11_13_18_01","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_spanish_uncased_2023_11_13_18_01","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_spanish_uncased_2023_11_13_18_01|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|250.2 MB|
+
+## References
+
+https://huggingface.co/Santp98/distilbert-base-spanish-uncased-2023-11-13-18-01
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_spanish_uncased_2023_11_13_18_01_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_spanish_uncased_2023_11_13_18_01_pipeline_en.md
new file mode 100644
index 00000000000000..02aed5c1eee056
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_spanish_uncased_2023_11_13_18_01_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_spanish_uncased_2023_11_13_18_01_pipeline pipeline DistilBertEmbeddings from Santp98
+author: John Snow Labs
+name: distilbert_base_spanish_uncased_2023_11_13_18_01_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_spanish_uncased_2023_11_13_18_01_pipeline` is a English model originally trained by Santp98.
+
+{:.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/distilbert_base_spanish_uncased_2023_11_13_18_01_pipeline_en_5.5.0_3.0_1725828935607.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_spanish_uncased_2023_11_13_18_01_pipeline_en_5.5.0_3.0_1725828935607.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
+
+pipeline = PretrainedPipeline("distilbert_base_spanish_uncased_2023_11_13_18_01_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_spanish_uncased_2023_11_13_18_01_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_spanish_uncased_2023_11_13_18_01_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|250.2 MB|
+
+## References
+
+https://huggingface.co/Santp98/distilbert-base-spanish-uncased-2023-11-13-18-01
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncase_english_hasoc_unethical_derogatory_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncase_english_hasoc_unethical_derogatory_pipeline_en.md
new file mode 100644
index 00000000000000..b004b968aa3416
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncase_english_hasoc_unethical_derogatory_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncase_english_hasoc_unethical_derogatory_pipeline pipeline RoBertaForSequenceClassification from jayanta
+author: John Snow Labs
+name: distilbert_base_uncase_english_hasoc_unethical_derogatory_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncase_english_hasoc_unethical_derogatory_pipeline` is a English model originally trained by jayanta.
+
+{:.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/distilbert_base_uncase_english_hasoc_unethical_derogatory_pipeline_en_5.5.0_3.0_1725830192536.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncase_english_hasoc_unethical_derogatory_pipeline_en_5.5.0_3.0_1725830192536.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncase_english_hasoc_unethical_derogatory_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncase_english_hasoc_unethical_derogatory_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncase_english_hasoc_unethical_derogatory_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/jayanta/distilbert-base-uncase-english-hasoc-unethical-derogatory
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_absa2016_laptop_v1_0_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_absa2016_laptop_v1_0_en.md
new file mode 100644
index 00000000000000..619c46f608d064
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_absa2016_laptop_v1_0_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_absa2016_laptop_v1_0 DistilBertForSequenceClassification from rajat33
+author: John Snow Labs
+name: distilbert_base_uncased_absa2016_laptop_v1_0
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_absa2016_laptop_v1_0` is a English model originally trained by rajat33.
+
+{:.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/distilbert_base_uncased_absa2016_laptop_v1_0_en_5.5.0_3.0_1725808713137.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_absa2016_laptop_v1_0_en_5.5.0_3.0_1725808713137.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_absa2016_laptop_v1_0","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_absa2016_laptop_v1_0", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_absa2016_laptop_v1_0|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/rajat33/distilbert-base-uncased-absa2016-laptop-v1.0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_distilled_clinc_esperesa_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_distilled_clinc_esperesa_en.md
new file mode 100644
index 00000000000000..ac79adf855d23a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_distilled_clinc_esperesa_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_distilled_clinc_esperesa DistilBertForSequenceClassification from esperesa
+author: John Snow Labs
+name: distilbert_base_uncased_distilled_clinc_esperesa
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_distilled_clinc_esperesa` is a English model originally trained by esperesa.
+
+{:.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/distilbert_base_uncased_distilled_clinc_esperesa_en_5.5.0_3.0_1725808697770.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_distilled_clinc_esperesa_en_5.5.0_3.0_1725808697770.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_distilled_clinc_esperesa","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_distilled_clinc_esperesa", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_distilled_clinc_esperesa|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.9 MB|
+
+## References
+
+https://huggingface.co/esperesa/distilbert-base-uncased-distilled-clinc
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_distilled_clinc_esperesa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_distilled_clinc_esperesa_pipeline_en.md
new file mode 100644
index 00000000000000..fca960fa42487a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_distilled_clinc_esperesa_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_distilled_clinc_esperesa_pipeline pipeline DistilBertForSequenceClassification from esperesa
+author: John Snow Labs
+name: distilbert_base_uncased_distilled_clinc_esperesa_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_distilled_clinc_esperesa_pipeline` is a English model originally trained by esperesa.
+
+{:.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/distilbert_base_uncased_distilled_clinc_esperesa_pipeline_en_5.5.0_3.0_1725808712164.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_distilled_clinc_esperesa_pipeline_en_5.5.0_3.0_1725808712164.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_distilled_clinc_esperesa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_distilled_clinc_esperesa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_distilled_clinc_esperesa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.9 MB|
+
+## References
+
+https://huggingface.co/esperesa/distilbert-base-uncased-distilled-clinc
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_clinc_tienle123_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_clinc_tienle123_pipeline_en.md
new file mode 100644
index 00000000000000..e802210ac08e06
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_clinc_tienle123_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_clinc_tienle123_pipeline pipeline DistilBertForSequenceClassification from Tienle123
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_clinc_tienle123_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_clinc_tienle123_pipeline` is a English model originally trained by Tienle123.
+
+{:.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/distilbert_base_uncased_finetuned_clinc_tienle123_pipeline_en_5.5.0_3.0_1725764254662.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_clinc_tienle123_pipeline_en_5.5.0_3.0_1725764254662.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_clinc_tienle123_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_clinc_tienle123_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_clinc_tienle123_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.9 MB|
+
+## References
+
+https://huggingface.co/Tienle123/distilbert-base-uncased-finetuned-clinc
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_cola_azadeh297_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_cola_azadeh297_en.md
new file mode 100644
index 00000000000000..d81fc491cc2b4c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_cola_azadeh297_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_cola_azadeh297 DistilBertForSequenceClassification from Azadeh297
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_cola_azadeh297
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_cola_azadeh297` is a English model originally trained by Azadeh297.
+
+{:.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/distilbert_base_uncased_finetuned_cola_azadeh297_en_5.5.0_3.0_1725776879734.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_azadeh297_en_5.5.0_3.0_1725776879734.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_cola_azadeh297","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_cola_azadeh297", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_cola_azadeh297|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Azadeh297/distilbert-base-uncased-finetuned-cola
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_cola_azadeh297_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_cola_azadeh297_pipeline_en.md
new file mode 100644
index 00000000000000..06181401829835
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_cola_azadeh297_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_cola_azadeh297_pipeline pipeline DistilBertForSequenceClassification from Azadeh297
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_cola_azadeh297_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_cola_azadeh297_pipeline` is a English model originally trained by Azadeh297.
+
+{:.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/distilbert_base_uncased_finetuned_cola_azadeh297_pipeline_en_5.5.0_3.0_1725776893044.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_azadeh297_pipeline_en_5.5.0_3.0_1725776893044.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_cola_azadeh297_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_cola_azadeh297_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_cola_azadeh297_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Azadeh297/distilbert-base-uncased-finetuned-cola
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_cola_rach_transformer_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_cola_rach_transformer_en.md
new file mode 100644
index 00000000000000..0bb2e74ec2d194
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_cola_rach_transformer_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_cola_rach_transformer DistilBertForSequenceClassification from rach-transformer
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_cola_rach_transformer
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_cola_rach_transformer` is a English model originally trained by rach-transformer.
+
+{:.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/distilbert_base_uncased_finetuned_cola_rach_transformer_en_5.5.0_3.0_1725776744695.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_cola_rach_transformer_en_5.5.0_3.0_1725776744695.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_cola_rach_transformer","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_cola_rach_transformer", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_cola_rach_transformer|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/rach-transformer/distilbert-base-uncased-finetuned-cola
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_discharge_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_discharge_en.md
new file mode 100644
index 00000000000000..d0e4fe4ff07318
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_discharge_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_discharge DistilBertForSequenceClassification from Reboot87
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_discharge
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_discharge` is a English model originally trained by Reboot87.
+
+{:.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/distilbert_base_uncased_finetuned_discharge_en_5.5.0_3.0_1725777411899.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_discharge_en_5.5.0_3.0_1725777411899.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_discharge","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_discharge", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_discharge|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Reboot87/distilbert-base-uncased-finetuned-discharge
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_discharge_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_discharge_pipeline_en.md
new file mode 100644
index 00000000000000..bd921e2b233c09
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_discharge_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_discharge_pipeline pipeline DistilBertForSequenceClassification from Reboot87
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_discharge_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_discharge_pipeline` is a English model originally trained by Reboot87.
+
+{:.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/distilbert_base_uncased_finetuned_discharge_pipeline_en_5.5.0_3.0_1725777424081.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_discharge_pipeline_en_5.5.0_3.0_1725777424081.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_discharge_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_discharge_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_discharge_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Reboot87/distilbert-base-uncased-finetuned-discharge
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_emotion_exam_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_emotion_exam_en.md
new file mode 100644
index 00000000000000..3717e95e0a1b35
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_emotion_exam_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_exam DistilBertForSequenceClassification from 888Brogaard
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_exam
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_exam` is a English model originally trained by 888Brogaard.
+
+{:.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/distilbert_base_uncased_finetuned_emotion_exam_en_5.5.0_3.0_1725808938700.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_exam_en_5.5.0_3.0_1725808938700.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_exam","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_exam", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_exam|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/888Brogaard/distilbert-base-uncased-finetuned-emotion-Exam
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_emotion_malay_5_0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_emotion_malay_5_0_pipeline_en.md
new file mode 100644
index 00000000000000..cb836735fad5a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_emotion_malay_5_0_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_malay_5_0_pipeline pipeline DistilBertForSequenceClassification from LeBruse
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_malay_5_0_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_malay_5_0_pipeline` is a English model originally trained by LeBruse.
+
+{:.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/distilbert_base_uncased_finetuned_emotion_malay_5_0_pipeline_en_5.5.0_3.0_1725775367768.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_malay_5_0_pipeline_en_5.5.0_3.0_1725775367768.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_malay_5_0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_malay_5_0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_malay_5_0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/LeBruse/distilbert-base-uncased-finetuned-emotion-malay-5.0
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_emotion_schnatz65_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_emotion_schnatz65_en.md
new file mode 100644
index 00000000000000..c2275900d587d1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_emotion_schnatz65_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_schnatz65 DistilBertForSequenceClassification from Schnatz65
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_schnatz65
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_schnatz65` is a English model originally trained by Schnatz65.
+
+{:.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/distilbert_base_uncased_finetuned_emotion_schnatz65_en_5.5.0_3.0_1725764628625.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_schnatz65_en_5.5.0_3.0_1725764628625.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_schnatz65","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_schnatz65", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_schnatz65|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Schnatz65/distilbert-base-uncased-finetuned-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_emotion_talzoomanzoo_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_emotion_talzoomanzoo_pipeline_en.md
new file mode 100644
index 00000000000000..b8832966e1e2c0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_emotion_talzoomanzoo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_talzoomanzoo_pipeline pipeline DistilBertForSequenceClassification from talzoomanzoo
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_talzoomanzoo_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_talzoomanzoo_pipeline` is a English model originally trained by talzoomanzoo.
+
+{:.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/distilbert_base_uncased_finetuned_emotion_talzoomanzoo_pipeline_en_5.5.0_3.0_1725764808321.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_talzoomanzoo_pipeline_en_5.5.0_3.0_1725764808321.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_talzoomanzoo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_talzoomanzoo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_talzoomanzoo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/talzoomanzoo/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_emotion_taoyoung_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_emotion_taoyoung_pipeline_en.md
new file mode 100644
index 00000000000000..9f6070e36df533
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_emotion_taoyoung_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_taoyoung_pipeline pipeline DistilBertForSequenceClassification from taoyoung
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_taoyoung_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_taoyoung_pipeline` is a English model originally trained by taoyoung.
+
+{:.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/distilbert_base_uncased_finetuned_emotion_taoyoung_pipeline_en_5.5.0_3.0_1725808518870.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_taoyoung_pipeline_en_5.5.0_3.0_1725808518870.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_taoyoung_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_taoyoung_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_taoyoung_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/taoyoung/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_ac729735256_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_ac729735256_en.md
new file mode 100644
index 00000000000000..921fd229a2e7dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_ac729735256_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_ac729735256 DistilBertEmbeddings from ac729735256
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_ac729735256
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_ac729735256` is a English model originally trained by ac729735256.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_ac729735256_en_5.5.0_3.0_1725782200460.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_ac729735256_en_5.5.0_3.0_1725782200460.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_ac729735256","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_ac729735256","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_ac729735256|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/ac729735256/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_ac729735256_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_ac729735256_pipeline_en.md
new file mode 100644
index 00000000000000..b2c6fab3afdeeb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_ac729735256_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_ac729735256_pipeline pipeline DistilBertEmbeddings from ac729735256
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_ac729735256_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_ac729735256_pipeline` is a English model originally trained by ac729735256.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_ac729735256_pipeline_en_5.5.0_3.0_1725782216442.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_ac729735256_pipeline_en_5.5.0_3.0_1725782216442.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_ac729735256_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_ac729735256_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_ac729735256_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/ac729735256/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_accelerate_aniruddh10124_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_accelerate_aniruddh10124_en.md
new file mode 100644
index 00000000000000..d96da8b4f44123
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_accelerate_aniruddh10124_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_accelerate_aniruddh10124 DistilBertEmbeddings from aniruddh10124
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_accelerate_aniruddh10124
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_accelerate_aniruddh10124` is a English model originally trained by aniruddh10124.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_accelerate_aniruddh10124_en_5.5.0_3.0_1725828384634.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_accelerate_aniruddh10124_en_5.5.0_3.0_1725828384634.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_accelerate_aniruddh10124","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_accelerate_aniruddh10124","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_accelerate_aniruddh10124|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/aniruddh10124/distilbert-base-uncased-finetuned-imdb-accelerate
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_accelerate_aniruddh10124_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_accelerate_aniruddh10124_pipeline_en.md
new file mode 100644
index 00000000000000..24d67ac3989b43
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_accelerate_aniruddh10124_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_accelerate_aniruddh10124_pipeline pipeline DistilBertEmbeddings from aniruddh10124
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_accelerate_aniruddh10124_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_accelerate_aniruddh10124_pipeline` is a English model originally trained by aniruddh10124.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_accelerate_aniruddh10124_pipeline_en_5.5.0_3.0_1725828397306.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_accelerate_aniruddh10124_pipeline_en_5.5.0_3.0_1725828397306.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_accelerate_aniruddh10124_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_accelerate_aniruddh10124_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_accelerate_aniruddh10124_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/aniruddh10124/distilbert-base-uncased-finetuned-imdb-accelerate
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_accelerate_minshengchan_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_accelerate_minshengchan_en.md
new file mode 100644
index 00000000000000..a550726874e0f2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_accelerate_minshengchan_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_accelerate_minshengchan DistilBertEmbeddings from minshengchan
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_accelerate_minshengchan
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_accelerate_minshengchan` is a English model originally trained by minshengchan.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_accelerate_minshengchan_en_5.5.0_3.0_1725782225596.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_accelerate_minshengchan_en_5.5.0_3.0_1725782225596.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_accelerate_minshengchan","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_accelerate_minshengchan","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_accelerate_minshengchan|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/minshengchan/distilbert-base-uncased-finetuned-imdb-accelerate
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_accelerate_phantatbach_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_accelerate_phantatbach_en.md
new file mode 100644
index 00000000000000..71b7746e191181
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_accelerate_phantatbach_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_accelerate_phantatbach DistilBertEmbeddings from phantatbach
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_accelerate_phantatbach
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_accelerate_phantatbach` is a English model originally trained by phantatbach.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_accelerate_phantatbach_en_5.5.0_3.0_1725782200313.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_accelerate_phantatbach_en_5.5.0_3.0_1725782200313.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_accelerate_phantatbach","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_accelerate_phantatbach","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_accelerate_phantatbach|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/phantatbach/distilbert-base-uncased-finetuned-imdb-accelerate
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_accelerate_xxxxxcz_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_accelerate_xxxxxcz_pipeline_en.md
new file mode 100644
index 00000000000000..c935657320135c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_accelerate_xxxxxcz_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_accelerate_xxxxxcz_pipeline pipeline DistilBertEmbeddings from xxxxxcz
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_accelerate_xxxxxcz_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_accelerate_xxxxxcz_pipeline` is a English model originally trained by xxxxxcz.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_accelerate_xxxxxcz_pipeline_en_5.5.0_3.0_1725828489616.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_accelerate_xxxxxcz_pipeline_en_5.5.0_3.0_1725828489616.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_accelerate_xxxxxcz_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_accelerate_xxxxxcz_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_accelerate_xxxxxcz_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/xxxxxcz/distilbert-base-uncased-finetuned-imdb-accelerate
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_banw_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_banw_en.md
new file mode 100644
index 00000000000000..ebf9fffe8e7872
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_banw_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_banw DistilBertEmbeddings from banw
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_banw
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_banw` is a English model originally trained by banw.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_banw_en_5.5.0_3.0_1725782595992.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_banw_en_5.5.0_3.0_1725782595992.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_banw","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_banw","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_banw|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/banw/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_chrischang80_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_chrischang80_en.md
new file mode 100644
index 00000000000000..9878d1c26f4196
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_chrischang80_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_chrischang80 DistilBertEmbeddings from chrischang80
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_chrischang80
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_chrischang80` is a English model originally trained by chrischang80.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_chrischang80_en_5.5.0_3.0_1725782748335.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_chrischang80_en_5.5.0_3.0_1725782748335.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_chrischang80","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_chrischang80","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_chrischang80|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/chrischang80/DistilBert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_dylettante_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_dylettante_en.md
new file mode 100644
index 00000000000000..48d1dfbc76f1b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_dylettante_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_dylettante DistilBertEmbeddings from Dylettante
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_dylettante
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_dylettante` is a English model originally trained by Dylettante.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_dylettante_en_5.5.0_3.0_1725782439917.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_dylettante_en_5.5.0_3.0_1725782439917.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_dylettante","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_dylettante","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_dylettante|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Dylettante/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_fah_d_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_fah_d_en.md
new file mode 100644
index 00000000000000..a3d56ea702c7c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_fah_d_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_fah_d DistilBertEmbeddings from Fah-d
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_fah_d
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_fah_d` is a English model originally trained by Fah-d.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_fah_d_en_5.5.0_3.0_1725782676409.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_fah_d_en_5.5.0_3.0_1725782676409.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_fah_d","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_fah_d","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_fah_d|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Fah-d/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_indah1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_indah1_pipeline_en.md
new file mode 100644
index 00000000000000..17a89ca7d34699
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_indah1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_indah1_pipeline pipeline DistilBertEmbeddings from Indah1
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_indah1_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_indah1_pipeline` is a English model originally trained by Indah1.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_indah1_pipeline_en_5.5.0_3.0_1725776171979.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_indah1_pipeline_en_5.5.0_3.0_1725776171979.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_indah1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_indah1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_indah1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Indah1/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_kapliff89_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_kapliff89_en.md
new file mode 100644
index 00000000000000..8e2321b2550a3f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_kapliff89_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_kapliff89 DistilBertEmbeddings from kapliff89
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_kapliff89
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_kapliff89` is a English model originally trained by kapliff89.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_kapliff89_en_5.5.0_3.0_1725782342919.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_kapliff89_en_5.5.0_3.0_1725782342919.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_kapliff89","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_kapliff89","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_kapliff89|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/kapliff89/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_kapliff89_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_kapliff89_pipeline_en.md
new file mode 100644
index 00000000000000..ef08227ddef12f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_kapliff89_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_kapliff89_pipeline pipeline DistilBertEmbeddings from kapliff89
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_kapliff89_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_kapliff89_pipeline` is a English model originally trained by kapliff89.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_kapliff89_pipeline_en_5.5.0_3.0_1725782354337.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_kapliff89_pipeline_en_5.5.0_3.0_1725782354337.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_kapliff89_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_kapliff89_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_kapliff89_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/kapliff89/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_konic_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_konic_en.md
new file mode 100644
index 00000000000000..98f29d17b648b2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_konic_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_konic DistilBertEmbeddings from Konic
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_konic
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_konic` is a English model originally trained by Konic.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_konic_en_5.5.0_3.0_1725828384723.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_konic_en_5.5.0_3.0_1725828384723.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_konic","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_konic","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_konic|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Konic/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_konic_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_konic_pipeline_en.md
new file mode 100644
index 00000000000000..c446834829f09e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_konic_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_konic_pipeline pipeline DistilBertEmbeddings from Konic
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_konic_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_konic_pipeline` is a English model originally trained by Konic.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_konic_pipeline_en_5.5.0_3.0_1725828398752.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_konic_pipeline_en_5.5.0_3.0_1725828398752.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_konic_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_konic_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_konic_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Konic/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_marcosautuori_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_marcosautuori_pipeline_en.md
new file mode 100644
index 00000000000000..39e89f183700dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_marcosautuori_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_marcosautuori_pipeline pipeline DistilBertEmbeddings from MarcosAutuori
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_marcosautuori_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_marcosautuori_pipeline` is a English model originally trained by MarcosAutuori.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_marcosautuori_pipeline_en_5.5.0_3.0_1725782421424.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_marcosautuori_pipeline_en_5.5.0_3.0_1725782421424.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_marcosautuori_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_marcosautuori_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_marcosautuori_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/MarcosAutuori/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_pbwinter_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_pbwinter_pipeline_en.md
new file mode 100644
index 00000000000000..655f843df9af2a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_pbwinter_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_pbwinter_pipeline pipeline DistilBertEmbeddings from pbwinter
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_pbwinter_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_pbwinter_pipeline` is a English model originally trained by pbwinter.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_pbwinter_pipeline_en_5.5.0_3.0_1725782541388.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_pbwinter_pipeline_en_5.5.0_3.0_1725782541388.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_pbwinter_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_pbwinter_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_pbwinter_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/pbwinter/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_sjunique_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_sjunique_en.md
new file mode 100644
index 00000000000000..951483d55b64db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_sjunique_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_sjunique DistilBertEmbeddings from sjunique
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_sjunique
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_sjunique` is a English model originally trained by sjunique.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_sjunique_en_5.5.0_3.0_1725828628394.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_sjunique_en_5.5.0_3.0_1725828628394.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_sjunique","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_sjunique","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_sjunique|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/sjunique/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_skyimple_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_skyimple_en.md
new file mode 100644
index 00000000000000..d2a51fd3e2fe0d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_skyimple_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_skyimple DistilBertEmbeddings from skyimple
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_skyimple
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_skyimple` is a English model originally trained by skyimple.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_skyimple_en_5.5.0_3.0_1725828914362.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_skyimple_en_5.5.0_3.0_1725828914362.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_skyimple","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_skyimple","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_skyimple|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/skyimple/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_soninimish_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_soninimish_en.md
new file mode 100644
index 00000000000000..ed7e5c4a263f09
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_soninimish_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_soninimish DistilBertEmbeddings from soninimish
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_soninimish
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_soninimish` is a English model originally trained by soninimish.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_soninimish_en_5.5.0_3.0_1725828578669.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_soninimish_en_5.5.0_3.0_1725828578669.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_soninimish","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_soninimish","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_soninimish|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/soninimish/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_soninimish_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_soninimish_pipeline_en.md
new file mode 100644
index 00000000000000..b6bda3497383b6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_soninimish_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_soninimish_pipeline pipeline DistilBertEmbeddings from soninimish
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_soninimish_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_soninimish_pipeline` is a English model originally trained by soninimish.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_soninimish_pipeline_en_5.5.0_3.0_1725828591024.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_soninimish_pipeline_en_5.5.0_3.0_1725828591024.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_soninimish_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_soninimish_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_soninimish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/soninimish/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_tim0207_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_tim0207_en.md
new file mode 100644
index 00000000000000..394cb7b670d463
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_tim0207_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_tim0207 DistilBertEmbeddings from Tim0207
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_tim0207
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_tim0207` is a English model originally trained by Tim0207.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_tim0207_en_5.5.0_3.0_1725828815280.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_tim0207_en_5.5.0_3.0_1725828815280.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_tim0207","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_tim0207","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_tim0207|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Tim0207/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_wjk233_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_wjk233_pipeline_en.md
new file mode 100644
index 00000000000000..216cb30e3d52cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_wjk233_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_wjk233_pipeline pipeline DistilBertEmbeddings from WJK233
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_wjk233_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_wjk233_pipeline` is a English model originally trained by WJK233.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_wjk233_pipeline_en_5.5.0_3.0_1725776240275.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_wjk233_pipeline_en_5.5.0_3.0_1725776240275.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_wjk233_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_wjk233_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_wjk233_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/WJK233/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_wwm_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_wwm_en.md
new file mode 100644
index 00000000000000..7bb9d513fe9178
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_wwm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_wwm DistilBertEmbeddings from chrischang80
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_wwm
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_wwm` is a English model originally trained by chrischang80.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_wwm_en_5.5.0_3.0_1725828774705.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_wwm_en_5.5.0_3.0_1725828774705.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_wwm","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_wwm","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_wwm|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/chrischang80/DistilBert-base-uncased-finetuned-imdb-wwm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_xxxxxcz_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_xxxxxcz_pipeline_en.md
new file mode 100644
index 00000000000000..e61db00827e19a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_imdb_xxxxxcz_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_xxxxxcz_pipeline pipeline DistilBertEmbeddings from xxxxxcz
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_xxxxxcz_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_xxxxxcz_pipeline` is a English model originally trained by xxxxxcz.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_xxxxxcz_pipeline_en_5.5.0_3.0_1725775902566.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_xxxxxcz_pipeline_en_5.5.0_3.0_1725775902566.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_xxxxxcz_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_xxxxxcz_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_xxxxxcz_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/xxxxxcz/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_ner_antoineedy_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_ner_antoineedy_pipeline_en.md
new file mode 100644
index 00000000000000..4e21d3cdd44799
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_ner_antoineedy_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_antoineedy_pipeline pipeline DistilBertForTokenClassification from antoineedy
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_antoineedy_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_antoineedy_pipeline` is a English model originally trained by antoineedy.
+
+{:.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/distilbert_base_uncased_finetuned_ner_antoineedy_pipeline_en_5.5.0_3.0_1725827826083.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_antoineedy_pipeline_en_5.5.0_3.0_1725827826083.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_antoineedy_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_antoineedy_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_antoineedy_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/antoineedy/distilbert-base-uncased-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_ner_bbmcmann_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_ner_bbmcmann_pipeline_en.md
new file mode 100644
index 00000000000000..dc268ae22bfcad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_ner_bbmcmann_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_bbmcmann_pipeline pipeline DistilBertForTokenClassification from bbmcmann
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_bbmcmann_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_bbmcmann_pipeline` is a English model originally trained by bbmcmann.
+
+{:.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/distilbert_base_uncased_finetuned_ner_bbmcmann_pipeline_en_5.5.0_3.0_1725827708215.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_bbmcmann_pipeline_en_5.5.0_3.0_1725827708215.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_bbmcmann_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_bbmcmann_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_bbmcmann_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/bbmcmann/distilbert-base-uncased-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_ner_gabescu_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_ner_gabescu_en.md
new file mode 100644
index 00000000000000..d61501017a4e8f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_ner_gabescu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_gabescu DistilBertForTokenClassification from Gabescu
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_gabescu
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_gabescu` is a English model originally trained by Gabescu.
+
+{:.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/distilbert_base_uncased_finetuned_ner_gabescu_en_5.5.0_3.0_1725827475553.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_gabescu_en_5.5.0_3.0_1725827475553.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_gabescu","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_gabescu", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_gabescu|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Gabescu/distilbert-base-uncased-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_ner_gabescu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_ner_gabescu_pipeline_en.md
new file mode 100644
index 00000000000000..a914cb0a1bd64c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_ner_gabescu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_gabescu_pipeline pipeline DistilBertForTokenClassification from Gabescu
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_gabescu_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_gabescu_pipeline` is a English model originally trained by Gabescu.
+
+{:.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/distilbert_base_uncased_finetuned_ner_gabescu_pipeline_en_5.5.0_3.0_1725827488270.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_gabescu_pipeline_en_5.5.0_3.0_1725827488270.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_gabescu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_gabescu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_gabescu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Gabescu/distilbert-base-uncased-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_ner_heclope_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_ner_heclope_en.md
new file mode 100644
index 00000000000000..192659fefd0cfb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_ner_heclope_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_heclope DistilBertForTokenClassification from heclope
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_heclope
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_heclope` is a English model originally trained by heclope.
+
+{:.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/distilbert_base_uncased_finetuned_ner_heclope_en_5.5.0_3.0_1725788747017.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_heclope_en_5.5.0_3.0_1725788747017.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_heclope","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_heclope", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_heclope|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/heclope/distilbert-base-uncased-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_ner_jbarnes_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_ner_jbarnes_pipeline_en.md
new file mode 100644
index 00000000000000..2f45999f73c85f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_ner_jbarnes_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_jbarnes_pipeline pipeline DistilBertForTokenClassification from jbarnes
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_jbarnes_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_jbarnes_pipeline` is a English model originally trained by jbarnes.
+
+{:.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/distilbert_base_uncased_finetuned_ner_jbarnes_pipeline_en_5.5.0_3.0_1725827886452.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_jbarnes_pipeline_en_5.5.0_3.0_1725827886452.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_jbarnes_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_jbarnes_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_jbarnes_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/jbarnes/distilbert-base-uncased-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_ner_sansan_9119_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_ner_sansan_9119_pipeline_en.md
new file mode 100644
index 00000000000000..ee66a27f4a911a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_ner_sansan_9119_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_sansan_9119_pipeline pipeline DistilBertForTokenClassification from SAnsAN-9119
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_sansan_9119_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_sansan_9119_pipeline` is a English model originally trained by SAnsAN-9119.
+
+{:.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/distilbert_base_uncased_finetuned_ner_sansan_9119_pipeline_en_5.5.0_3.0_1725788388716.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_sansan_9119_pipeline_en_5.5.0_3.0_1725788388716.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_ner_sansan_9119_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_ner_sansan_9119_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_sansan_9119_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/SAnsAN-9119/distilbert-base-uncased-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_ner_whoopwhoop_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_ner_whoopwhoop_en.md
new file mode 100644
index 00000000000000..648170e2567c23
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_ner_whoopwhoop_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_ner_whoopwhoop DistilBertForTokenClassification from whoopwhoop
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_ner_whoopwhoop
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_ner_whoopwhoop` is a English model originally trained by whoopwhoop.
+
+{:.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/distilbert_base_uncased_finetuned_ner_whoopwhoop_en_5.5.0_3.0_1725788936681.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_ner_whoopwhoop_en_5.5.0_3.0_1725788936681.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_whoopwhoop","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_base_uncased_finetuned_ner_whoopwhoop", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_ner_whoopwhoop|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/whoopwhoop/distilbert-base-uncased-finetuned-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_news_articles_arsruts_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_news_articles_arsruts_pipeline_en.md
new file mode 100644
index 00000000000000..2e1484498c83cd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_news_articles_arsruts_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_news_articles_arsruts_pipeline pipeline DistilBertForSequenceClassification from arsruts
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_news_articles_arsruts_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_news_articles_arsruts_pipeline` is a English model originally trained by arsruts.
+
+{:.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/distilbert_base_uncased_finetuned_news_articles_arsruts_pipeline_en_5.5.0_3.0_1725777345768.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_news_articles_arsruts_pipeline_en_5.5.0_3.0_1725777345768.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_news_articles_arsruts_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_news_articles_arsruts_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_news_articles_arsruts_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/arsruts/distilbert-base-uncased-finetuned_news_articles
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_squad_d5716d28_dadbear_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_squad_d5716d28_dadbear_en.md
new file mode 100644
index 00000000000000..cfe0764c1f218b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_squad_d5716d28_dadbear_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_d5716d28_dadbear DistilBertForQuestionAnswering from dadbear
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_d5716d28_dadbear
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_d5716d28_dadbear` is a English model originally trained by dadbear.
+
+{:.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/distilbert_base_uncased_finetuned_squad_d5716d28_dadbear_en_5.5.0_3.0_1725798482296.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_d5716d28_dadbear_en_5.5.0_3.0_1725798482296.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_d5716d28_dadbear","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_d5716d28_dadbear", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_d5716d28_dadbear|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/dadbear/distilbert-base-uncased-finetuned-squad-d5716d28
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_squad_d5716d28_ysugawa_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_squad_d5716d28_ysugawa_en.md
new file mode 100644
index 00000000000000..49f9dfb93b9dc4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_squad_d5716d28_ysugawa_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_d5716d28_ysugawa DistilBertEmbeddings from ysugawa
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_d5716d28_ysugawa
+date: 2024-09-08
+tags: [distilbert, en, open_source, fill_mask, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings  model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_d5716d28_ysugawa` is a English model originally trained by ysugawa.
+
+## 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/distilbert_base_uncased_finetuned_squad_d5716d28_ysugawa_en_5.5.0_3.0_1725798212694.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_d5716d28_ysugawa_en_5.5.0_3.0_1725798212694.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 =DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_squad_d5716d28_ysugawa","en") \
+            .setInputCols(["documents","token"]) \
+            .setOutputCol("embeddings")
+
+pipeline = Pipeline().setStages([document_assembler, embeddings])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("embeddings")
+    
+val embeddings = DistilBertEmbeddings 
+    .pretrained("distilbert_base_uncased_finetuned_squad_d5716d28_ysugawa", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("embeddings") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_d5716d28_ysugawa|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+References
+
+https://huggingface.co/ysugawa/distilbert-base-uncased-finetuned-squad-d5716d28
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_squad_d5716d28_ysugawa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_squad_d5716d28_ysugawa_pipeline_en.md
new file mode 100644
index 00000000000000..83e6c779cdefb2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_squad_d5716d28_ysugawa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_d5716d28_ysugawa_pipeline pipeline DistilBertForQuestionAnswering from ysugawa
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_d5716d28_ysugawa_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_d5716d28_ysugawa_pipeline` is a English model originally trained by ysugawa.
+
+{:.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/distilbert_base_uncased_finetuned_squad_d5716d28_ysugawa_pipeline_en_5.5.0_3.0_1725798224538.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_d5716d28_ysugawa_pipeline_en_5.5.0_3.0_1725798224538.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_d5716d28_ysugawa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_d5716d28_ysugawa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_d5716d28_ysugawa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/ysugawa/distilbert-base-uncased-finetuned-squad-d5716d28
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_squad_d5716d28_yukihirop_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_squad_d5716d28_yukihirop_pipeline_en.md
new file mode 100644
index 00000000000000..fd904ec31210f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_squad_d5716d28_yukihirop_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_d5716d28_yukihirop_pipeline pipeline DistilBertForQuestionAnswering from yukihirop
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_d5716d28_yukihirop_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_d5716d28_yukihirop_pipeline` is a English model originally trained by yukihirop.
+
+{:.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/distilbert_base_uncased_finetuned_squad_d5716d28_yukihirop_pipeline_en_5.5.0_3.0_1725823600509.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_d5716d28_yukihirop_pipeline_en_5.5.0_3.0_1725823600509.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_d5716d28_yukihirop_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_d5716d28_yukihirop_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_d5716d28_yukihirop_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/yukihirop/distilbert-base-uncased-finetuned-squad-d5716d28
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_squad_inaspin_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_squad_inaspin_en.md
new file mode 100644
index 00000000000000..34ed8c7d3c7c68
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_squad_inaspin_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_inaspin DistilBertForQuestionAnswering from inaspin
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_inaspin
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_inaspin` is a English model originally trained by inaspin.
+
+{:.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/distilbert_base_uncased_finetuned_squad_inaspin_en_5.5.0_3.0_1725818033897.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_inaspin_en_5.5.0_3.0_1725818033897.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_inaspin","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_inaspin", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_inaspin|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/inaspin/distilbert-base-uncased-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_squad_patrikrac_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_squad_patrikrac_pipeline_en.md
new file mode 100644
index 00000000000000..4b1fd185c1f69e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_squad_patrikrac_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_patrikrac_pipeline pipeline DistilBertForQuestionAnswering from patrikrac
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_patrikrac_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_patrikrac_pipeline` is a English model originally trained by patrikrac.
+
+{:.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/distilbert_base_uncased_finetuned_squad_patrikrac_pipeline_en_5.5.0_3.0_1725798088781.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_patrikrac_pipeline_en_5.5.0_3.0_1725798088781.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_patrikrac_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_patrikrac_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_patrikrac_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/patrikrac/distilbert-base-uncased-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_squad_taeseon_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_squad_taeseon_pipeline_en.md
new file mode 100644
index 00000000000000..dc71988828d2e0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_squad_taeseon_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_taeseon_pipeline pipeline DistilBertForQuestionAnswering from taeseon
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_taeseon_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_taeseon_pipeline` is a English model originally trained by taeseon.
+
+{:.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/distilbert_base_uncased_finetuned_squad_taeseon_pipeline_en_5.5.0_3.0_1725818628974.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_taeseon_pipeline_en_5.5.0_3.0_1725818628974.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_taeseon_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_taeseon_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_taeseon_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/taeseon/distilbert-base-uncased-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_stsb_elyziumm_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_stsb_elyziumm_pipeline_en.md
new file mode 100644
index 00000000000000..55fdcc517486f6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_finetuned_stsb_elyziumm_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_stsb_elyziumm_pipeline pipeline DistilBertForSequenceClassification from elyziumm
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_stsb_elyziumm_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_stsb_elyziumm_pipeline` is a English model originally trained by elyziumm.
+
+{:.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/distilbert_base_uncased_finetuned_stsb_elyziumm_pipeline_en_5.5.0_3.0_1725776892848.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_stsb_elyziumm_pipeline_en_5.5.0_3.0_1725776892848.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_stsb_elyziumm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_stsb_elyziumm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_stsb_elyziumm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/elyziumm/distilbert-base-uncased-finetuned-stsb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_org_address_question_answering_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_org_address_question_answering_en.md
new file mode 100644
index 00000000000000..1cbd2a002ead97
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_org_address_question_answering_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_base_uncased_org_address_question_answering DistilBertForQuestionAnswering from mansee
+author: John Snow Labs
+name: distilbert_base_uncased_org_address_question_answering
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_org_address_question_answering` is a English model originally trained by mansee.
+
+{:.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/distilbert_base_uncased_org_address_question_answering_en_5.5.0_3.0_1725818268113.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_org_address_question_answering_en_5.5.0_3.0_1725818268113.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_org_address_question_answering","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_org_address_question_answering", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_org_address_question_answering|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/mansee/distilbert-base-uncased-org-address-question-answering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_squad2_p25_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_squad2_p25_en.md
new file mode 100644
index 00000000000000..9a11eaae43d9a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_squad2_p25_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_base_uncased_squad2_p25 DistilBertForQuestionAnswering from pminha
+author: John Snow Labs
+name: distilbert_base_uncased_squad2_p25
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_squad2_p25` is a English model originally trained by pminha.
+
+{:.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/distilbert_base_uncased_squad2_p25_en_5.5.0_3.0_1725798273033.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_squad2_p25_en_5.5.0_3.0_1725798273033.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_squad2_p25","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_squad2_p25", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_squad2_p25|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|219.6 MB|
+
+## References
+
+https://huggingface.co/pminha/distilbert-base-uncased-squad2-p25
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_squad2_p25_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_squad2_p25_pipeline_en.md
new file mode 100644
index 00000000000000..fe9eeec238482f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_squad2_p25_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_squad2_p25_pipeline pipeline DistilBertForQuestionAnswering from pminha
+author: John Snow Labs
+name: distilbert_base_uncased_squad2_p25_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_squad2_p25_pipeline` is a English model originally trained by pminha.
+
+{:.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/distilbert_base_uncased_squad2_p25_pipeline_en_5.5.0_3.0_1725798286961.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_squad2_p25_pipeline_en_5.5.0_3.0_1725798286961.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_squad2_p25_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_squad2_p25_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_squad2_p25_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|219.6 MB|
+
+## References
+
+https://huggingface.co/pminha/distilbert-base-uncased-squad2-p25
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_whole_word_finetuned_imdb_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_whole_word_finetuned_imdb_en.md
new file mode 100644
index 00000000000000..8c8b23c9e960d8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_whole_word_finetuned_imdb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_whole_word_finetuned_imdb DistilBertEmbeddings from StrawHatDrag0n
+author: John Snow Labs
+name: distilbert_base_uncased_whole_word_finetuned_imdb
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_whole_word_finetuned_imdb` is a English model originally trained by StrawHatDrag0n.
+
+{:.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/distilbert_base_uncased_whole_word_finetuned_imdb_en_5.5.0_3.0_1725782315218.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_whole_word_finetuned_imdb_en_5.5.0_3.0_1725782315218.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_whole_word_finetuned_imdb","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_whole_word_finetuned_imdb","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_whole_word_finetuned_imdb|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/StrawHatDrag0n/distilbert-base-uncased-whole-word-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_whole_word_finetuned_imdb_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_whole_word_finetuned_imdb_pipeline_en.md
new file mode 100644
index 00000000000000..8eb9d70e5341b3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_base_uncased_whole_word_finetuned_imdb_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_whole_word_finetuned_imdb_pipeline pipeline DistilBertEmbeddings from StrawHatDrag0n
+author: John Snow Labs
+name: distilbert_base_uncased_whole_word_finetuned_imdb_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_whole_word_finetuned_imdb_pipeline` is a English model originally trained by StrawHatDrag0n.
+
+{:.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/distilbert_base_uncased_whole_word_finetuned_imdb_pipeline_en_5.5.0_3.0_1725782327943.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_whole_word_finetuned_imdb_pipeline_en_5.5.0_3.0_1725782327943.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_whole_word_finetuned_imdb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_whole_word_finetuned_imdb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_whole_word_finetuned_imdb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/StrawHatDrag0n/distilbert-base-uncased-whole-word-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_cord_ner_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_cord_ner_en.md
new file mode 100644
index 00000000000000..040329233b6ed2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_cord_ner_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_cord_ner DistilBertForTokenClassification from renjithks
+author: John Snow Labs
+name: distilbert_cord_ner
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_cord_ner` is a English model originally trained by renjithks.
+
+{:.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/distilbert_cord_ner_en_5.5.0_3.0_1725837276237.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_cord_ner_en_5.5.0_3.0_1725837276237.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("distilbert_cord_ner","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_cord_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_cord_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|280.9 MB|
+
+## References
+
+https://huggingface.co/renjithks/distilbert-cord-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_dair_ai_emotion_20240730_e2_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_dair_ai_emotion_20240730_e2_en.md
new file mode 100644
index 00000000000000..a76bc0e7c88287
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_dair_ai_emotion_20240730_e2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_dair_ai_emotion_20240730_e2 DistilBertForSequenceClassification from Chahnwoo
+author: John Snow Labs
+name: distilbert_dair_ai_emotion_20240730_e2
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_dair_ai_emotion_20240730_e2` is a English model originally trained by Chahnwoo.
+
+{:.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/distilbert_dair_ai_emotion_20240730_e2_en_5.5.0_3.0_1725777500237.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_dair_ai_emotion_20240730_e2_en_5.5.0_3.0_1725777500237.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_dair_ai_emotion_20240730_e2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_dair_ai_emotion_20240730_e2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_dair_ai_emotion_20240730_e2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Chahnwoo/distilbert_dair-ai_emotion_20240730_e2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_finetuned_squad_noushsuon_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_finetuned_squad_noushsuon_pipeline_en.md
new file mode 100644
index 00000000000000..b3035bcc87ee0f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_finetuned_squad_noushsuon_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_finetuned_squad_noushsuon_pipeline pipeline DistilBertForQuestionAnswering from noushsuon
+author: John Snow Labs
+name: distilbert_finetuned_squad_noushsuon_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_squad_noushsuon_pipeline` is a English model originally trained by noushsuon.
+
+{:.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/distilbert_finetuned_squad_noushsuon_pipeline_en_5.5.0_3.0_1725798244234.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_squad_noushsuon_pipeline_en_5.5.0_3.0_1725798244234.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
+
+pipeline = PretrainedPipeline("distilbert_finetuned_squad_noushsuon_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_finetuned_squad_noushsuon_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_squad_noushsuon_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/noushsuon/distilbert-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_finetuned_squadv2_dungquarkquark_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_finetuned_squadv2_dungquarkquark_pipeline_en.md
new file mode 100644
index 00000000000000..9b0efa202e189d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_finetuned_squadv2_dungquarkquark_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_finetuned_squadv2_dungquarkquark_pipeline pipeline DistilBertForQuestionAnswering from dungquarkquark
+author: John Snow Labs
+name: distilbert_finetuned_squadv2_dungquarkquark_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_squadv2_dungquarkquark_pipeline` is a English model originally trained by dungquarkquark.
+
+{:.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/distilbert_finetuned_squadv2_dungquarkquark_pipeline_en_5.5.0_3.0_1725823681150.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_squadv2_dungquarkquark_pipeline_en_5.5.0_3.0_1725823681150.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
+
+pipeline = PretrainedPipeline("distilbert_finetuned_squadv2_dungquarkquark_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_finetuned_squadv2_dungquarkquark_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_squadv2_dungquarkquark_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/dungquarkquark/distilbert-finetuned-squadv2
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_finetuned_squadv2_levancuong17_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_finetuned_squadv2_levancuong17_en.md
new file mode 100644
index 00000000000000..7e049eff3bebde
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_finetuned_squadv2_levancuong17_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_finetuned_squadv2_levancuong17 DistilBertForQuestionAnswering from levancuong17
+author: John Snow Labs
+name: distilbert_finetuned_squadv2_levancuong17
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_squadv2_levancuong17` is a English model originally trained by levancuong17.
+
+{:.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/distilbert_finetuned_squadv2_levancuong17_en_5.5.0_3.0_1725798119265.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_squadv2_levancuong17_en_5.5.0_3.0_1725798119265.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_finetuned_squadv2_levancuong17","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_finetuned_squadv2_levancuong17", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_squadv2_levancuong17|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/levancuong17/distilbert-finetuned-squadv2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_finetuned_squadv2_zoanhy_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_finetuned_squadv2_zoanhy_en.md
new file mode 100644
index 00000000000000..6ed0acaddbc559
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_finetuned_squadv2_zoanhy_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_finetuned_squadv2_zoanhy DistilBertForQuestionAnswering from zoanhy
+author: John Snow Labs
+name: distilbert_finetuned_squadv2_zoanhy
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_finetuned_squadv2_zoanhy` is a English model originally trained by zoanhy.
+
+{:.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/distilbert_finetuned_squadv2_zoanhy_en_5.5.0_3.0_1725818525013.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_finetuned_squadv2_zoanhy_en_5.5.0_3.0_1725818525013.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_finetuned_squadv2_zoanhy","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_finetuned_squadv2_zoanhy", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_finetuned_squadv2_zoanhy|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/zoanhy/distilbert-finetuned-squadv2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_heaps_half_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_heaps_half_pipeline_en.md
new file mode 100644
index 00000000000000..c16105a4615d72
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_heaps_half_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_heaps_half_pipeline pipeline DistilBertEmbeddings from johannes-garstenauer
+author: John Snow Labs
+name: distilbert_heaps_half_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_heaps_half_pipeline` is a English model originally trained by johannes-garstenauer.
+
+{:.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/distilbert_heaps_half_pipeline_en_5.5.0_3.0_1725776418968.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_heaps_half_pipeline_en_5.5.0_3.0_1725776418968.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
+
+pipeline = PretrainedPipeline("distilbert_heaps_half_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_heaps_half_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_heaps_half_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.9 MB|
+
+## References
+
+https://huggingface.co/johannes-garstenauer/distilbert-heaps-half
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_masking_simplified_2_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_masking_simplified_2_en.md
new file mode 100644
index 00000000000000..ade4a13c7b8c7d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_masking_simplified_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_masking_simplified_2 DistilBertEmbeddings from johannes-garstenauer
+author: John Snow Labs
+name: distilbert_masking_simplified_2
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_masking_simplified_2` is a English model originally trained by johannes-garstenauer.
+
+{:.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/distilbert_masking_simplified_2_en_5.5.0_3.0_1725782539071.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_masking_simplified_2_en_5.5.0_3.0_1725782539071.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_masking_simplified_2","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_masking_simplified_2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_masking_simplified_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|248.6 MB|
+
+## References
+
+https://huggingface.co/johannes-garstenauer/distilbert_masking-simplified_2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_movie_review_sentiment_classifier_3_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_movie_review_sentiment_classifier_3_en.md
new file mode 100644
index 00000000000000..3c3fcf66b57171
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_movie_review_sentiment_classifier_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_movie_review_sentiment_classifier_3 DistilBertForSequenceClassification from gyesibiney
+author: John Snow Labs
+name: distilbert_movie_review_sentiment_classifier_3
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_movie_review_sentiment_classifier_3` is a English model originally trained by gyesibiney.
+
+{:.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/distilbert_movie_review_sentiment_classifier_3_en_5.5.0_3.0_1725777373532.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_movie_review_sentiment_classifier_3_en_5.5.0_3.0_1725777373532.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_movie_review_sentiment_classifier_3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_movie_review_sentiment_classifier_3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_movie_review_sentiment_classifier_3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|250.9 MB|
+
+## References
+
+https://huggingface.co/gyesibiney/Distilbert-movie-review-sentiment-classifier-3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_ndd_html_content_tags_multiclass_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_ndd_html_content_tags_multiclass_en.md
new file mode 100644
index 00000000000000..8cf7ca33d63dbb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_ndd_html_content_tags_multiclass_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_ndd_html_content_tags_multiclass DistilBertForSequenceClassification from lgk03
+author: John Snow Labs
+name: distilbert_ndd_html_content_tags_multiclass
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ndd_html_content_tags_multiclass` is a English model originally trained by lgk03.
+
+{:.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/distilbert_ndd_html_content_tags_multiclass_en_5.5.0_3.0_1725808506457.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ndd_html_content_tags_multiclass_en_5.5.0_3.0_1725808506457.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_ndd_html_content_tags_multiclass","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_ndd_html_content_tags_multiclass", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_ndd_html_content_tags_multiclass|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lgk03/distilBERT-NDD.html.content_tags_multiclass
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_qa_squad_english_german_spanish_model_xx.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_qa_squad_english_german_spanish_model_xx.md
new file mode 100644
index 00000000000000..640530bb29e57e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_qa_squad_english_german_spanish_model_xx.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Multilingual distilbert_qa_squad_english_german_spanish_model DistilBertForQuestionAnswering from ZYW
+author: John Snow Labs
+name: distilbert_qa_squad_english_german_spanish_model
+date: 2024-09-08
+tags: [xx, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_qa_squad_english_german_spanish_model` is a Multilingual model originally trained by ZYW.
+
+{:.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/distilbert_qa_squad_english_german_spanish_model_xx_5.5.0_3.0_1725818235462.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_qa_squad_english_german_spanish_model_xx_5.5.0_3.0_1725818235462.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_qa_squad_english_german_spanish_model","xx") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_qa_squad_english_german_spanish_model", "xx")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_qa_squad_english_german_spanish_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|xx|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/ZYW/squad-en-de-es-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_sanskrit_saskta_glue_experiment_logit_kd_cola_384_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_sanskrit_saskta_glue_experiment_logit_kd_cola_384_pipeline_en.md
new file mode 100644
index 00000000000000..f924ac9ff45a85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_sanskrit_saskta_glue_experiment_logit_kd_cola_384_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_sanskrit_saskta_glue_experiment_logit_kd_cola_384_pipeline pipeline DistilBertForSequenceClassification from gokuls
+author: John Snow Labs
+name: distilbert_sanskrit_saskta_glue_experiment_logit_kd_cola_384_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_sanskrit_saskta_glue_experiment_logit_kd_cola_384_pipeline` is a English model originally trained by gokuls.
+
+{:.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/distilbert_sanskrit_saskta_glue_experiment_logit_kd_cola_384_pipeline_en_5.5.0_3.0_1725764574231.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_sanskrit_saskta_glue_experiment_logit_kd_cola_384_pipeline_en_5.5.0_3.0_1725764574231.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
+
+pipeline = PretrainedPipeline("distilbert_sanskrit_saskta_glue_experiment_logit_kd_cola_384_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_sanskrit_saskta_glue_experiment_logit_kd_cola_384_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_sanskrit_saskta_glue_experiment_logit_kd_cola_384_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|111.8 MB|
+
+## References
+
+https://huggingface.co/gokuls/distilbert_sa_GLUE_Experiment_logit_kd_cola_384
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_sanskrit_saskta_glue_experiment_qnli_384_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_sanskrit_saskta_glue_experiment_qnli_384_en.md
new file mode 100644
index 00000000000000..42247449e43b2a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_sanskrit_saskta_glue_experiment_qnli_384_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_sanskrit_saskta_glue_experiment_qnli_384 DistilBertForSequenceClassification from gokuls
+author: John Snow Labs
+name: distilbert_sanskrit_saskta_glue_experiment_qnli_384
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_sanskrit_saskta_glue_experiment_qnli_384` is a English model originally trained by gokuls.
+
+{:.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/distilbert_sanskrit_saskta_glue_experiment_qnli_384_en_5.5.0_3.0_1725777403296.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_sanskrit_saskta_glue_experiment_qnli_384_en_5.5.0_3.0_1725777403296.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_sanskrit_saskta_glue_experiment_qnli_384","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_sanskrit_saskta_glue_experiment_qnli_384", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_sanskrit_saskta_glue_experiment_qnli_384|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|111.8 MB|
+
+## References
+
+https://huggingface.co/gokuls/distilbert_sa_GLUE_Experiment_qnli_384
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_sanskrit_saskta_glue_experiment_qnli_384_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_sanskrit_saskta_glue_experiment_qnli_384_pipeline_en.md
new file mode 100644
index 00000000000000..30658e39c49ee0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_sanskrit_saskta_glue_experiment_qnli_384_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_sanskrit_saskta_glue_experiment_qnli_384_pipeline pipeline DistilBertForSequenceClassification from gokuls
+author: John Snow Labs
+name: distilbert_sanskrit_saskta_glue_experiment_qnli_384_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_sanskrit_saskta_glue_experiment_qnli_384_pipeline` is a English model originally trained by gokuls.
+
+{:.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/distilbert_sanskrit_saskta_glue_experiment_qnli_384_pipeline_en_5.5.0_3.0_1725777408675.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_sanskrit_saskta_glue_experiment_qnli_384_pipeline_en_5.5.0_3.0_1725777408675.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
+
+pipeline = PretrainedPipeline("distilbert_sanskrit_saskta_glue_experiment_qnli_384_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_sanskrit_saskta_glue_experiment_qnli_384_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_sanskrit_saskta_glue_experiment_qnli_384_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|111.9 MB|
+
+## References
+
+https://huggingface.co/gokuls/distilbert_sa_GLUE_Experiment_qnli_384
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_squad2_dynamic_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_squad2_dynamic_en.md
new file mode 100644
index 00000000000000..2ddcfb5b4aa3e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_squad2_dynamic_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_squad2_dynamic DistilBertForQuestionAnswering from jysh1023
+author: John Snow Labs
+name: distilbert_squad2_dynamic
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_squad2_dynamic` is a English model originally trained by jysh1023.
+
+{:.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/distilbert_squad2_dynamic_en_5.5.0_3.0_1725818418108.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_squad2_dynamic_en_5.5.0_3.0_1725818418108.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_squad2_dynamic","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_squad2_dynamic", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_squad2_dynamic|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|243.9 MB|
+
+## References
+
+https://huggingface.co/jysh1023/distilbert_squad2_dynamic
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_squad2_dynamic_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_squad2_dynamic_pipeline_en.md
new file mode 100644
index 00000000000000..3f7d3fb33c1250
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_squad2_dynamic_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_squad2_dynamic_pipeline pipeline DistilBertForQuestionAnswering from jysh1023
+author: John Snow Labs
+name: distilbert_squad2_dynamic_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_squad2_dynamic_pipeline` is a English model originally trained by jysh1023.
+
+{:.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/distilbert_squad2_dynamic_pipeline_en_5.5.0_3.0_1725818430296.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_squad2_dynamic_pipeline_en_5.5.0_3.0_1725818430296.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
+
+pipeline = PretrainedPipeline("distilbert_squad2_dynamic_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_squad2_dynamic_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_squad2_dynamic_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.9 MB|
+
+## References
+
+https://huggingface.co/jysh1023/distilbert_squad2_dynamic
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_suicide_detection_hk_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_suicide_detection_hk_pipeline_en.md
new file mode 100644
index 00000000000000..819139a3353751
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_suicide_detection_hk_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_suicide_detection_hk_pipeline pipeline DistilBertForSequenceClassification from wcyat
+author: John Snow Labs
+name: distilbert_suicide_detection_hk_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_suicide_detection_hk_pipeline` is a English model originally trained by wcyat.
+
+{:.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/distilbert_suicide_detection_hk_pipeline_en_5.5.0_3.0_1725775387191.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_suicide_detection_hk_pipeline_en_5.5.0_3.0_1725775387191.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
+
+pipeline = PretrainedPipeline("distilbert_suicide_detection_hk_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_suicide_detection_hk_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_suicide_detection_hk_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/wcyat/distilbert-suicide-detection-hk
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_tok_classifier_typo_detector_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_tok_classifier_typo_detector_en.md
new file mode 100644
index 00000000000000..67ea7a74580fc1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_tok_classifier_typo_detector_en.md
@@ -0,0 +1,100 @@
+---
+layout: model
+title: English DistilBertForTokenClassification Cased model (from m3hrdadfi)
+author: John Snow Labs
+name: distilbert_tok_classifier_typo_detector
+date: 2024-09-08
+tags: [en, open_source, distilbert, token_classification, ner, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `typo-detector-distilbert-en` is a English model originally trained by `m3hrdadfi`.
+
+## Predicted Entities
+
+`TYPO`
+
+{:.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/distilbert_tok_classifier_typo_detector_en_5.5.0_3.0_1725788439206.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_tok_classifier_typo_detector_en_5.5.0_3.0_1725788439206.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
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_tok_classifier_typo_detector","en") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, tokenClassifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+    .setInputCol("text")
+    .setOutputCol("document")
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("distilbert_tok_classifier_typo_detector","en")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_tok_classifier_typo_detector|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+References
+
+- https://huggingface.co/m3hrdadfi/typo-detector-distilbert-en
+- https://github.com/neuspell/neuspell
+- https://github.com/m3hrdadfi/typo-detector/issues
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_tok_classifier_typo_detector_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_tok_classifier_typo_detector_pipeline_en.md
new file mode 100644
index 00000000000000..5e16ad05e415c9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_tok_classifier_typo_detector_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_tok_classifier_typo_detector_pipeline pipeline DistilBertForTokenClassification from m3hrdadfi
+author: John Snow Labs
+name: distilbert_tok_classifier_typo_detector_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_tok_classifier_typo_detector_pipeline` is a English model originally trained by m3hrdadfi.
+
+{:.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/distilbert_tok_classifier_typo_detector_pipeline_en_5.5.0_3.0_1725788451393.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_tok_classifier_typo_detector_pipeline_en_5.5.0_3.0_1725788451393.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
+
+pipeline = PretrainedPipeline("distilbert_tok_classifier_typo_detector_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_tok_classifier_typo_detector_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_tok_classifier_typo_detector_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/m3hrdadfi/typo-detector-distilbert-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilbert_tweet_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilbert_tweet_en.md
new file mode 100644
index 00000000000000..7279222f4745d7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilbert_tweet_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_tweet DistilBertForSequenceClassification from Sangmitra-06
+author: John Snow Labs
+name: distilbert_tweet
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_tweet` is a English model originally trained by Sangmitra-06.
+
+{:.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/distilbert_tweet_en_5.5.0_3.0_1725775454855.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_tweet_en_5.5.0_3.0_1725775454855.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilbert_tweet","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_tweet", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_tweet|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Sangmitra-06/DistilBERT_tweet
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilibert_finetuned_squadv2_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilibert_finetuned_squadv2_en.md
new file mode 100644
index 00000000000000..83fa512637f4b8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilibert_finetuned_squadv2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilibert_finetuned_squadv2 DistilBertForQuestionAnswering from d4rk3r
+author: John Snow Labs
+name: distilibert_finetuned_squadv2
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilibert_finetuned_squadv2` is a English model originally trained by d4rk3r.
+
+{:.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/distilibert_finetuned_squadv2_en_5.5.0_3.0_1725818529508.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilibert_finetuned_squadv2_en_5.5.0_3.0_1725818529508.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilibert_finetuned_squadv2","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilibert_finetuned_squadv2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilibert_finetuned_squadv2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/d4rk3r/distilibert-finetuned-squadv2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilibert_finetuned_squadv2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilibert_finetuned_squadv2_pipeline_en.md
new file mode 100644
index 00000000000000..04820db81a36c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilibert_finetuned_squadv2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilibert_finetuned_squadv2_pipeline pipeline DistilBertForQuestionAnswering from d4rk3r
+author: John Snow Labs
+name: distilibert_finetuned_squadv2_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilibert_finetuned_squadv2_pipeline` is a English model originally trained by d4rk3r.
+
+{:.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/distilibert_finetuned_squadv2_pipeline_en_5.5.0_3.0_1725818544214.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilibert_finetuned_squadv2_pipeline_en_5.5.0_3.0_1725818544214.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
+
+pipeline = PretrainedPipeline("distilibert_finetuned_squadv2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilibert_finetuned_squadv2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilibert_finetuned_squadv2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/d4rk3r/distilibert-finetuned-squadv2
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilled_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilled_bert_pipeline_en.md
new file mode 100644
index 00000000000000..e0802a3d0a649d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilled_bert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilled_bert_pipeline pipeline DistilBertForTokenClassification from Gkumi
+author: John Snow Labs
+name: distilled_bert_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilled_bert_pipeline` is a English model originally trained by Gkumi.
+
+{:.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/distilled_bert_pipeline_en_5.5.0_3.0_1725827392322.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilled_bert_pipeline_en_5.5.0_3.0_1725827392322.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
+
+pipeline = PretrainedPipeline("distilled_bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilled_bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilled_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|244.1 MB|
+
+## References
+
+https://huggingface.co/Gkumi/distilled-bert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilled_optimized_indobert_classification_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilled_optimized_indobert_classification_en.md
new file mode 100644
index 00000000000000..9cb5337da38dca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilled_optimized_indobert_classification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilled_optimized_indobert_classification DistilBertForSequenceClassification from afbudiman
+author: John Snow Labs
+name: distilled_optimized_indobert_classification
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilled_optimized_indobert_classification` is a English model originally trained by afbudiman.
+
+{:.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/distilled_optimized_indobert_classification_en_5.5.0_3.0_1725777473195.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilled_optimized_indobert_classification_en_5.5.0_3.0_1725777473195.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("distilled_optimized_indobert_classification","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilled_optimized_indobert_classification", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilled_optimized_indobert_classification|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/afbudiman/distilled-optimized-indobert-classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilled_optimized_indobert_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilled_optimized_indobert_classification_pipeline_en.md
new file mode 100644
index 00000000000000..87b6914e8c618a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilled_optimized_indobert_classification_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilled_optimized_indobert_classification_pipeline pipeline DistilBertForSequenceClassification from afbudiman
+author: John Snow Labs
+name: distilled_optimized_indobert_classification_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilled_optimized_indobert_classification_pipeline` is a English model originally trained by afbudiman.
+
+{:.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/distilled_optimized_indobert_classification_pipeline_en_5.5.0_3.0_1725777485265.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilled_optimized_indobert_classification_pipeline_en_5.5.0_3.0_1725777485265.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
+
+pipeline = PretrainedPipeline("distilled_optimized_indobert_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilled_optimized_indobert_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilled_optimized_indobert_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/afbudiman/distilled-optimized-indobert-classification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilroberta_base_finetuned_short_answer_assessment_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilroberta_base_finetuned_short_answer_assessment_en.md
new file mode 100644
index 00000000000000..8c5435298f7096
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilroberta_base_finetuned_short_answer_assessment_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilroberta_base_finetuned_short_answer_assessment RoBertaForSequenceClassification from Giyaseddin
+author: John Snow Labs
+name: distilroberta_base_finetuned_short_answer_assessment
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_finetuned_short_answer_assessment` is a English model originally trained by Giyaseddin.
+
+{:.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/distilroberta_base_finetuned_short_answer_assessment_en_5.5.0_3.0_1725829585675.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_finetuned_short_answer_assessment_en_5.5.0_3.0_1725829585675.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("distilroberta_base_finetuned_short_answer_assessment","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("distilroberta_base_finetuned_short_answer_assessment", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_finetuned_short_answer_assessment|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|308.8 MB|
+
+## References
+
+https://huggingface.co/Giyaseddin/distilroberta-base-finetuned-short-answer-assessment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilroberta_base_finetuned_short_answer_assessment_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilroberta_base_finetuned_short_answer_assessment_pipeline_en.md
new file mode 100644
index 00000000000000..1ffa0f5ad7ba99
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilroberta_base_finetuned_short_answer_assessment_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilroberta_base_finetuned_short_answer_assessment_pipeline pipeline RoBertaForSequenceClassification from Giyaseddin
+author: John Snow Labs
+name: distilroberta_base_finetuned_short_answer_assessment_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_finetuned_short_answer_assessment_pipeline` is a English model originally trained by Giyaseddin.
+
+{:.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/distilroberta_base_finetuned_short_answer_assessment_pipeline_en_5.5.0_3.0_1725829601556.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_finetuned_short_answer_assessment_pipeline_en_5.5.0_3.0_1725829601556.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
+
+pipeline = PretrainedPipeline("distilroberta_base_finetuned_short_answer_assessment_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilroberta_base_finetuned_short_answer_assessment_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_finetuned_short_answer_assessment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|308.8 MB|
+
+## References
+
+https://huggingface.co/Giyaseddin/distilroberta-base-finetuned-short-answer-assessment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilroberta_base_finetuned_winogrande_debiased_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilroberta_base_finetuned_winogrande_debiased_en.md
new file mode 100644
index 00000000000000..5f116bafcf42ce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilroberta_base_finetuned_winogrande_debiased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilroberta_base_finetuned_winogrande_debiased RoBertaForSequenceClassification from bpark5233
+author: John Snow Labs
+name: distilroberta_base_finetuned_winogrande_debiased
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_finetuned_winogrande_debiased` is a English model originally trained by bpark5233.
+
+{:.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/distilroberta_base_finetuned_winogrande_debiased_en_5.5.0_3.0_1725831027444.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_finetuned_winogrande_debiased_en_5.5.0_3.0_1725831027444.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("distilroberta_base_finetuned_winogrande_debiased","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("distilroberta_base_finetuned_winogrande_debiased", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_base_finetuned_winogrande_debiased|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|308.7 MB|
+
+## References
+
+https://huggingface.co/bpark5233/distilroberta-base-finetuned-winogrande_debiased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilroberta_rbm231k_ep20_op40_news_api_all_5p1k_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilroberta_rbm231k_ep20_op40_news_api_all_5p1k_en.md
new file mode 100644
index 00000000000000..e2df1ea5212205
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilroberta_rbm231k_ep20_op40_news_api_all_5p1k_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilroberta_rbm231k_ep20_op40_news_api_all_5p1k RoBertaForSequenceClassification from judy93536
+author: John Snow Labs
+name: distilroberta_rbm231k_ep20_op40_news_api_all_5p1k
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_rbm231k_ep20_op40_news_api_all_5p1k` is a English model originally trained by judy93536.
+
+{:.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/distilroberta_rbm231k_ep20_op40_news_api_all_5p1k_en_5.5.0_3.0_1725830293113.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_rbm231k_ep20_op40_news_api_all_5p1k_en_5.5.0_3.0_1725830293113.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("distilroberta_rbm231k_ep20_op40_news_api_all_5p1k","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("distilroberta_rbm231k_ep20_op40_news_api_all_5p1k", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_rbm231k_ep20_op40_news_api_all_5p1k|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|308.6 MB|
+
+## References
+
+https://huggingface.co/judy93536/distilroberta-rbm231k-ep20-op40-news_api_all_5p1k
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-distilroberta_rbm231k_ep20_op40_news_api_all_5p1k_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-distilroberta_rbm231k_ep20_op40_news_api_all_5p1k_pipeline_en.md
new file mode 100644
index 00000000000000..90dd37da9d15ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-distilroberta_rbm231k_ep20_op40_news_api_all_5p1k_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilroberta_rbm231k_ep20_op40_news_api_all_5p1k_pipeline pipeline RoBertaForSequenceClassification from judy93536
+author: John Snow Labs
+name: distilroberta_rbm231k_ep20_op40_news_api_all_5p1k_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_rbm231k_ep20_op40_news_api_all_5p1k_pipeline` is a English model originally trained by judy93536.
+
+{:.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/distilroberta_rbm231k_ep20_op40_news_api_all_5p1k_pipeline_en_5.5.0_3.0_1725830308084.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_rbm231k_ep20_op40_news_api_all_5p1k_pipeline_en_5.5.0_3.0_1725830308084.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
+
+pipeline = PretrainedPipeline("distilroberta_rbm231k_ep20_op40_news_api_all_5p1k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilroberta_rbm231k_ep20_op40_news_api_all_5p1k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilroberta_rbm231k_ep20_op40_news_api_all_5p1k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|308.6 MB|
+
+## References
+
+https://huggingface.co/judy93536/distilroberta-rbm231k-ep20-op40-news_api_all_5p1k
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-dock_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-dock_2_pipeline_en.md
new file mode 100644
index 00000000000000..64684b24e848ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-dock_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dock_2_pipeline pipeline RoBertaForSequenceClassification from BaronSch
+author: John Snow Labs
+name: dock_2_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dock_2_pipeline` is a English model originally trained by BaronSch.
+
+{:.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/dock_2_pipeline_en_5.5.0_3.0_1725820997565.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dock_2_pipeline_en_5.5.0_3.0_1725820997565.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
+
+pipeline = PretrainedPipeline("dock_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dock_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dock_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.5 MB|
+
+## References
+
+https://huggingface.co/BaronSch/Dock_2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-dstc_setfit_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-dstc_setfit_pipeline_en.md
new file mode 100644
index 00000000000000..3a7cd3cc33c437
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-dstc_setfit_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English dstc_setfit_pipeline pipeline MPNetEmbeddings from hxssgaa
+author: John Snow Labs
+name: dstc_setfit_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dstc_setfit_pipeline` is a English model originally trained by hxssgaa.
+
+{:.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/dstc_setfit_pipeline_en_5.5.0_3.0_1725816590769.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dstc_setfit_pipeline_en_5.5.0_3.0_1725816590769.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
+
+pipeline = PretrainedPipeline("dstc_setfit_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dstc_setfit_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dstc_setfit_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/hxssgaa/dstc_setfit
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-dummy_model_8mly_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_8mly_pipeline_en.md
new file mode 100644
index 00000000000000..4c8794581a2b5f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_8mly_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_8mly_pipeline pipeline CamemBertEmbeddings from mdroth
+author: John Snow Labs
+name: dummy_model_8mly_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_8mly_pipeline` is a English model originally trained by mdroth.
+
+{:.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/dummy_model_8mly_pipeline_en_5.5.0_3.0_1725836092729.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_8mly_pipeline_en_5.5.0_3.0_1725836092729.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
+
+pipeline = PretrainedPipeline("dummy_model_8mly_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_8mly_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_8mly_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/mdroth/dummy-model_8MlY
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-dummy_model_akkasayaz_en.md b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_akkasayaz_en.md
new file mode 100644
index 00000000000000..978b27b88c339a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_akkasayaz_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_akkasayaz CamemBertEmbeddings from akkasayaz
+author: John Snow Labs
+name: dummy_model_akkasayaz
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_akkasayaz` is a English model originally trained by akkasayaz.
+
+{:.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/dummy_model_akkasayaz_en_5.5.0_3.0_1725835971274.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_akkasayaz_en_5.5.0_3.0_1725835971274.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_akkasayaz","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_akkasayaz","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_akkasayaz|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/akkasayaz/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-dummy_model_bellylee_en.md b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_bellylee_en.md
new file mode 100644
index 00000000000000..07c18f2869427d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_bellylee_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_bellylee CamemBertEmbeddings from bellylee
+author: John Snow Labs
+name: dummy_model_bellylee
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_bellylee` is a English model originally trained by bellylee.
+
+{:.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/dummy_model_bellylee_en_5.5.0_3.0_1725786283648.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_bellylee_en_5.5.0_3.0_1725786283648.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_bellylee","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_bellylee","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_bellylee|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/bellylee/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-dummy_model_botmync_en.md b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_botmync_en.md
new file mode 100644
index 00000000000000..5c6b43d0d13349
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_botmync_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_botmync CamemBertEmbeddings from botMync
+author: John Snow Labs
+name: dummy_model_botmync
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_botmync` is a English model originally trained by botMync.
+
+{:.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/dummy_model_botmync_en_5.5.0_3.0_1725835740658.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_botmync_en_5.5.0_3.0_1725835740658.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_botmync","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_botmync","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_botmync|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/botMync/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-dummy_model_ccyr119_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_ccyr119_pipeline_en.md
new file mode 100644
index 00000000000000..ac8538cc720dc4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_ccyr119_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_ccyr119_pipeline pipeline CamemBertEmbeddings from ccyr119
+author: John Snow Labs
+name: dummy_model_ccyr119_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_ccyr119_pipeline` is a English model originally trained by ccyr119.
+
+{:.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/dummy_model_ccyr119_pipeline_en_5.5.0_3.0_1725836683974.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_ccyr119_pipeline_en_5.5.0_3.0_1725836683974.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
+
+pipeline = PretrainedPipeline("dummy_model_ccyr119_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_ccyr119_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_ccyr119_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/ccyr119/dummy_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-dummy_model_diya2002_en.md b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_diya2002_en.md
new file mode 100644
index 00000000000000..3f186ccf08aea4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_diya2002_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_diya2002 CamemBertEmbeddings from diya2002
+author: John Snow Labs
+name: dummy_model_diya2002
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_diya2002` is a English model originally trained by diya2002.
+
+{:.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/dummy_model_diya2002_en_5.5.0_3.0_1725836288609.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_diya2002_en_5.5.0_3.0_1725836288609.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_diya2002","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_diya2002","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_diya2002|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/diya2002/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-dummy_model_diya2002_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_diya2002_pipeline_en.md
new file mode 100644
index 00000000000000..9d3e662a869a1a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_diya2002_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_diya2002_pipeline pipeline CamemBertEmbeddings from diya2002
+author: John Snow Labs
+name: dummy_model_diya2002_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_diya2002_pipeline` is a English model originally trained by diya2002.
+
+{:.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/dummy_model_diya2002_pipeline_en_5.5.0_3.0_1725836364533.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_diya2002_pipeline_en_5.5.0_3.0_1725836364533.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
+
+pipeline = PretrainedPipeline("dummy_model_diya2002_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_diya2002_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_diya2002_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/diya2002/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-dummy_model_edward47_en.md b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_edward47_en.md
new file mode 100644
index 00000000000000..2b995963efa8b4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_edward47_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_edward47 CamemBertEmbeddings from Edward47
+author: John Snow Labs
+name: dummy_model_edward47
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_edward47` is a English model originally trained by Edward47.
+
+{:.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/dummy_model_edward47_en_5.5.0_3.0_1725836509651.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_edward47_en_5.5.0_3.0_1725836509651.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_edward47","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_edward47","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_edward47|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Edward47/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-dummy_model_edward47_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_edward47_pipeline_en.md
new file mode 100644
index 00000000000000..2d4e4a07cb8784
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_edward47_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_edward47_pipeline pipeline CamemBertEmbeddings from Edward47
+author: John Snow Labs
+name: dummy_model_edward47_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_edward47_pipeline` is a English model originally trained by Edward47.
+
+{:.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/dummy_model_edward47_pipeline_en_5.5.0_3.0_1725836587140.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_edward47_pipeline_en_5.5.0_3.0_1725836587140.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
+
+pipeline = PretrainedPipeline("dummy_model_edward47_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_edward47_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_edward47_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Edward47/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-dummy_model_elusive_magnolia_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_elusive_magnolia_pipeline_en.md
new file mode 100644
index 00000000000000..7ba243bdbb582a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_elusive_magnolia_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_elusive_magnolia_pipeline pipeline CamemBertEmbeddings from elusive-magnolia
+author: John Snow Labs
+name: dummy_model_elusive_magnolia_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_elusive_magnolia_pipeline` is a English model originally trained by elusive-magnolia.
+
+{:.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/dummy_model_elusive_magnolia_pipeline_en_5.5.0_3.0_1725786940827.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_elusive_magnolia_pipeline_en_5.5.0_3.0_1725786940827.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
+
+pipeline = PretrainedPipeline("dummy_model_elusive_magnolia_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_elusive_magnolia_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_elusive_magnolia_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/elusive-magnolia/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-dummy_model_iliyaml_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_iliyaml_pipeline_en.md
new file mode 100644
index 00000000000000..6f37ce418d49ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_iliyaml_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_iliyaml_pipeline pipeline CamemBertEmbeddings from iliyaML
+author: John Snow Labs
+name: dummy_model_iliyaml_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_iliyaml_pipeline` is a English model originally trained by iliyaML.
+
+{:.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/dummy_model_iliyaml_pipeline_en_5.5.0_3.0_1725786805830.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_iliyaml_pipeline_en_5.5.0_3.0_1725786805830.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
+
+pipeline = PretrainedPipeline("dummy_model_iliyaml_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_iliyaml_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_iliyaml_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/iliyaML/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-dummy_model_jiuthy_en.md b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_jiuthy_en.md
new file mode 100644
index 00000000000000..e435691180991d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_jiuthy_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_jiuthy CamemBertEmbeddings from jiuthy
+author: John Snow Labs
+name: dummy_model_jiuthy
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jiuthy` is a English model originally trained by jiuthy.
+
+{:.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/dummy_model_jiuthy_en_5.5.0_3.0_1725835973688.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jiuthy_en_5.5.0_3.0_1725835973688.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_jiuthy","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_jiuthy","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_jiuthy|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/jiuthy/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-dummy_model_jiuthy_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_jiuthy_pipeline_en.md
new file mode 100644
index 00000000000000..d03e1f5d75fea8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_jiuthy_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_jiuthy_pipeline pipeline CamemBertEmbeddings from jiuthy
+author: John Snow Labs
+name: dummy_model_jiuthy_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jiuthy_pipeline` is a English model originally trained by jiuthy.
+
+{:.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/dummy_model_jiuthy_pipeline_en_5.5.0_3.0_1725836051059.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jiuthy_pipeline_en_5.5.0_3.0_1725836051059.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
+
+pipeline = PretrainedPipeline("dummy_model_jiuthy_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_jiuthy_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_jiuthy_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/jiuthy/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-dummy_model_larrydai_en.md b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_larrydai_en.md
new file mode 100644
index 00000000000000..4915d0c348200d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_larrydai_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_larrydai CamemBertEmbeddings from larrydai
+author: John Snow Labs
+name: dummy_model_larrydai
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_larrydai` is a English model originally trained by larrydai.
+
+{:.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/dummy_model_larrydai_en_5.5.0_3.0_1725835742738.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_larrydai_en_5.5.0_3.0_1725835742738.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_larrydai","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_larrydai","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_larrydai|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/larrydai/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-dummy_model_ligut14789_en.md b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_ligut14789_en.md
new file mode 100644
index 00000000000000..7f2d217a10d604
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_ligut14789_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_ligut14789 CamemBertEmbeddings from ligut14789
+author: John Snow Labs
+name: dummy_model_ligut14789
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_ligut14789` is a English model originally trained by ligut14789.
+
+{:.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/dummy_model_ligut14789_en_5.5.0_3.0_1725836248627.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_ligut14789_en_5.5.0_3.0_1725836248627.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_ligut14789","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_ligut14789","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_ligut14789|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/ligut14789/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-dummy_model_ligut14789_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_ligut14789_pipeline_en.md
new file mode 100644
index 00000000000000..a275b597ead1e4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_ligut14789_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_ligut14789_pipeline pipeline CamemBertEmbeddings from ligut14789
+author: John Snow Labs
+name: dummy_model_ligut14789_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_ligut14789_pipeline` is a English model originally trained by ligut14789.
+
+{:.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/dummy_model_ligut14789_pipeline_en_5.5.0_3.0_1725836323574.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_ligut14789_pipeline_en_5.5.0_3.0_1725836323574.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
+
+pipeline = PretrainedPipeline("dummy_model_ligut14789_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_ligut14789_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_ligut14789_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/ligut14789/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-dummy_model_mbateman_en.md b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_mbateman_en.md
new file mode 100644
index 00000000000000..dbc5c7932955f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_mbateman_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_mbateman CamemBertEmbeddings from mbateman
+author: John Snow Labs
+name: dummy_model_mbateman
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_mbateman` is a English model originally trained by mbateman.
+
+{:.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/dummy_model_mbateman_en_5.5.0_3.0_1725786279091.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_mbateman_en_5.5.0_3.0_1725786279091.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_mbateman","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_mbateman","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_mbateman|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/mbateman/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-dummy_model_mnslarcher_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_mnslarcher_pipeline_en.md
new file mode 100644
index 00000000000000..dfab1827033fa6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_mnslarcher_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_mnslarcher_pipeline pipeline CamemBertEmbeddings from mnslarcher
+author: John Snow Labs
+name: dummy_model_mnslarcher_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_mnslarcher_pipeline` is a English model originally trained by mnslarcher.
+
+{:.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/dummy_model_mnslarcher_pipeline_en_5.5.0_3.0_1725786817533.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_mnslarcher_pipeline_en_5.5.0_3.0_1725786817533.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
+
+pipeline = PretrainedPipeline("dummy_model_mnslarcher_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_mnslarcher_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_mnslarcher_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/mnslarcher/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-dummy_model_muntasirtiash_en.md b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_muntasirtiash_en.md
new file mode 100644
index 00000000000000..63c5ed17b1e189
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_muntasirtiash_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_muntasirtiash CamemBertEmbeddings from MuntasirTiash
+author: John Snow Labs
+name: dummy_model_muntasirtiash
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_muntasirtiash` is a English model originally trained by MuntasirTiash.
+
+{:.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/dummy_model_muntasirtiash_en_5.5.0_3.0_1725835741087.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_muntasirtiash_en_5.5.0_3.0_1725835741087.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_muntasirtiash","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_muntasirtiash","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_muntasirtiash|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/MuntasirTiash/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-dummy_model_nskamal_en.md b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_nskamal_en.md
new file mode 100644
index 00000000000000..a33e4463fdb35c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_nskamal_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_nskamal CamemBertEmbeddings from nskamal
+author: John Snow Labs
+name: dummy_model_nskamal
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_nskamal` is a English model originally trained by nskamal.
+
+{:.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/dummy_model_nskamal_en_5.5.0_3.0_1725786280722.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_nskamal_en_5.5.0_3.0_1725786280722.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_nskamal","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_nskamal","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_nskamal|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/nskamal/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-dummy_model_rworm_en.md b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_rworm_en.md
new file mode 100644
index 00000000000000..671bb3579b1426
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_rworm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_rworm CamemBertEmbeddings from rworm
+author: John Snow Labs
+name: dummy_model_rworm
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_rworm` is a English model originally trained by rworm.
+
+{:.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/dummy_model_rworm_en_5.5.0_3.0_1725836695302.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_rworm_en_5.5.0_3.0_1725836695302.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_rworm","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_rworm","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_rworm|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/rworm/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-dummy_model_subhasree_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_subhasree_pipeline_en.md
new file mode 100644
index 00000000000000..ca02be53b957ae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_subhasree_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_subhasree_pipeline pipeline CamemBertEmbeddings from subhasree
+author: John Snow Labs
+name: dummy_model_subhasree_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_subhasree_pipeline` is a English model originally trained by subhasree.
+
+{:.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/dummy_model_subhasree_pipeline_en_5.5.0_3.0_1725836716482.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_subhasree_pipeline_en_5.5.0_3.0_1725836716482.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
+
+pipeline = PretrainedPipeline("dummy_model_subhasree_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_subhasree_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_subhasree_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/subhasree/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-dummy_model_vccler_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_vccler_pipeline_en.md
new file mode 100644
index 00000000000000..146a134cdf6867
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_vccler_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_vccler_pipeline pipeline CamemBertEmbeddings from vccler
+author: John Snow Labs
+name: dummy_model_vccler_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_vccler_pipeline` is a English model originally trained by vccler.
+
+{:.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/dummy_model_vccler_pipeline_en_5.5.0_3.0_1725787304760.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_vccler_pipeline_en_5.5.0_3.0_1725787304760.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
+
+pipeline = PretrainedPipeline("dummy_model_vccler_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_vccler_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_vccler_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/vccler/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-dummy_model_yuwei2342_en.md b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_yuwei2342_en.md
new file mode 100644
index 00000000000000..1c734cbb682fce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-dummy_model_yuwei2342_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_yuwei2342 CamemBertEmbeddings from yuwei2342
+author: John Snow Labs
+name: dummy_model_yuwei2342
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_yuwei2342` is a English model originally trained by yuwei2342.
+
+{:.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/dummy_model_yuwei2342_en_5.5.0_3.0_1725836160875.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_yuwei2342_en_5.5.0_3.0_1725836160875.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_yuwei2342","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_yuwei2342","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_yuwei2342|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/yuwei2342/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-ea_setfit_v1_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-ea_setfit_v1_classifier_pipeline_en.md
new file mode 100644
index 00000000000000..72d036c0422996
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-ea_setfit_v1_classifier_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English ea_setfit_v1_classifier_pipeline pipeline MPNetEmbeddings from czesty
+author: John Snow Labs
+name: ea_setfit_v1_classifier_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ea_setfit_v1_classifier_pipeline` is a English model originally trained by czesty.
+
+{:.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/ea_setfit_v1_classifier_pipeline_en_5.5.0_3.0_1725769519209.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ea_setfit_v1_classifier_pipeline_en_5.5.0_3.0_1725769519209.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
+
+pipeline = PretrainedPipeline("ea_setfit_v1_classifier_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ea_setfit_v1_classifier_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ea_setfit_v1_classifier_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/czesty/ea-setfit-v1-classifier
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-early_readmission_deberta_en.md b/docs/_posts/ahmedlone127/2024-09-08-early_readmission_deberta_en.md
new file mode 100644
index 00000000000000..b3df7dd8ab70a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-early_readmission_deberta_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English early_readmission_deberta DeBertaForSequenceClassification from austin
+author: John Snow Labs
+name: early_readmission_deberta
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`early_readmission_deberta` is a English model originally trained by austin.
+
+{:.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/early_readmission_deberta_en_5.5.0_3.0_1725804252470.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/early_readmission_deberta_en_5.5.0_3.0_1725804252470.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("early_readmission_deberta","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("early_readmission_deberta", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|early_readmission_deberta|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|607.5 MB|
+
+## References
+
+https://huggingface.co/austin/early-readmission-deberta
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-electra_classifier_korean_senti_1_ko.md b/docs/_posts/ahmedlone127/2024-09-08-electra_classifier_korean_senti_1_ko.md
new file mode 100644
index 00000000000000..9321c9d0b9ae47
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-electra_classifier_korean_senti_1_ko.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Korean electra_classifier_korean_senti_1 BertForSequenceClassification from heoji
+author: John Snow Labs
+name: electra_classifier_korean_senti_1
+date: 2024-09-08
+tags: [ko, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: ko
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`electra_classifier_korean_senti_1` is a Korean model originally trained by heoji.
+
+{:.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/electra_classifier_korean_senti_1_ko_5.5.0_3.0_1725761362974.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_classifier_korean_senti_1_ko_5.5.0_3.0_1725761362974.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("electra_classifier_korean_senti_1","ko") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("electra_classifier_korean_senti_1", "ko")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_classifier_korean_senti_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|ko|
+|Size:|414.5 MB|
+
+## References
+
+https://huggingface.co/heoji/koelectra_senti_1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-embed_andegpt_h768_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-08-embed_andegpt_h768_pipeline_es.md
new file mode 100644
index 00000000000000..9145efb9f61000
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-embed_andegpt_h768_pipeline_es.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Castilian, Spanish embed_andegpt_h768_pipeline pipeline MPNetEmbeddings from enpaiva
+author: John Snow Labs
+name: embed_andegpt_h768_pipeline
+date: 2024-09-08
+tags: [es, open_source, pipeline, onnx]
+task: Embeddings
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`embed_andegpt_h768_pipeline` is a Castilian, Spanish model originally trained by enpaiva.
+
+{:.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/embed_andegpt_h768_pipeline_es_5.5.0_3.0_1725815157827.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/embed_andegpt_h768_pipeline_es_5.5.0_3.0_1725815157827.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
+
+pipeline = PretrainedPipeline("embed_andegpt_h768_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("embed_andegpt_h768_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|embed_andegpt_h768_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|379.4 MB|
+
+## References
+
+https://huggingface.co/enpaiva/embed-andegpt-H768
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-emoji_emoji_temporal_roberta_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-emoji_emoji_temporal_roberta_base_pipeline_en.md
new file mode 100644
index 00000000000000..aac04863c61200
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-emoji_emoji_temporal_roberta_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English emoji_emoji_temporal_roberta_base_pipeline pipeline RoBertaForSequenceClassification from tweettemposhift
+author: John Snow Labs
+name: emoji_emoji_temporal_roberta_base_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`emoji_emoji_temporal_roberta_base_pipeline` is a English model originally trained by tweettemposhift.
+
+{:.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/emoji_emoji_temporal_roberta_base_pipeline_en_5.5.0_3.0_1725829609321.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/emoji_emoji_temporal_roberta_base_pipeline_en_5.5.0_3.0_1725829609321.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
+
+pipeline = PretrainedPipeline("emoji_emoji_temporal_roberta_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("emoji_emoji_temporal_roberta_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|emoji_emoji_temporal_roberta_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|450.7 MB|
+
+## References
+
+https://huggingface.co/tweettemposhift/emoji-emoji_temporal-roberta-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-enestranslatorforsummaries_en.md b/docs/_posts/ahmedlone127/2024-09-08-enestranslatorforsummaries_en.md
new file mode 100644
index 00000000000000..9c34923edac9e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-enestranslatorforsummaries_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English enestranslatorforsummaries MarianTransformer from sfarjebespalaia
+author: John Snow Labs
+name: enestranslatorforsummaries
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`enestranslatorforsummaries` is a English model originally trained by sfarjebespalaia.
+
+{:.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/enestranslatorforsummaries_en_5.5.0_3.0_1725765940233.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/enestranslatorforsummaries_en_5.5.0_3.0_1725765940233.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("enestranslatorforsummaries","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("enestranslatorforsummaries","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|enestranslatorforsummaries|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|539.9 MB|
+
+## References
+
+https://huggingface.co/sfarjebespalaia/enestranslatorforsummaries
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-enestranslatorforsummaries_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-enestranslatorforsummaries_pipeline_en.md
new file mode 100644
index 00000000000000..dce4c699e7d11b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-enestranslatorforsummaries_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English enestranslatorforsummaries_pipeline pipeline MarianTransformer from sfarjebespalaia
+author: John Snow Labs
+name: enestranslatorforsummaries_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`enestranslatorforsummaries_pipeline` is a English model originally trained by sfarjebespalaia.
+
+{:.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/enestranslatorforsummaries_pipeline_en_5.5.0_3.0_1725765966325.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/enestranslatorforsummaries_pipeline_en_5.5.0_3.0_1725765966325.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
+
+pipeline = PretrainedPipeline("enestranslatorforsummaries_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("enestranslatorforsummaries_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|enestranslatorforsummaries_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|540.4 MB|
+
+## References
+
+https://huggingface.co/sfarjebespalaia/enestranslatorforsummaries
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-english_tonga_tonga_islands_darija_2_en.md b/docs/_posts/ahmedlone127/2024-09-08-english_tonga_tonga_islands_darija_2_en.md
new file mode 100644
index 00000000000000..9ed4b5776b6c28
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-english_tonga_tonga_islands_darija_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English english_tonga_tonga_islands_darija_2 MarianTransformer from ychafiqui
+author: John Snow Labs
+name: english_tonga_tonga_islands_darija_2
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_tonga_tonga_islands_darija_2` is a English model originally trained by ychafiqui.
+
+{:.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/english_tonga_tonga_islands_darija_2_en_5.5.0_3.0_1725796456008.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_darija_2_en_5.5.0_3.0_1725796456008.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("english_tonga_tonga_islands_darija_2","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("english_tonga_tonga_islands_darija_2","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_tonga_tonga_islands_darija_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|1.4 GB|
+
+## References
+
+https://huggingface.co/ychafiqui/english-to-darija-2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-english_tonga_tonga_islands_darija_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-english_tonga_tonga_islands_darija_2_pipeline_en.md
new file mode 100644
index 00000000000000..9eea1111e72511
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-english_tonga_tonga_islands_darija_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English english_tonga_tonga_islands_darija_2_pipeline pipeline MarianTransformer from ychafiqui
+author: John Snow Labs
+name: english_tonga_tonga_islands_darija_2_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_tonga_tonga_islands_darija_2_pipeline` is a English model originally trained by ychafiqui.
+
+{:.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/english_tonga_tonga_islands_darija_2_pipeline_en_5.5.0_3.0_1725796517860.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_tonga_tonga_islands_darija_2_pipeline_en_5.5.0_3.0_1725796517860.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
+
+pipeline = PretrainedPipeline("english_tonga_tonga_islands_darija_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("english_tonga_tonga_islands_darija_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_tonga_tonga_islands_darija_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.4 GB|
+
+## References
+
+https://huggingface.co/ychafiqui/english-to-darija-2
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-english_vietnamese_maltese_model_en.md b/docs/_posts/ahmedlone127/2024-09-08-english_vietnamese_maltese_model_en.md
new file mode 100644
index 00000000000000..8ba05925903fa7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-english_vietnamese_maltese_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English english_vietnamese_maltese_model MarianTransformer from haotieu
+author: John Snow Labs
+name: english_vietnamese_maltese_model
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_vietnamese_maltese_model` is a English model originally trained by haotieu.
+
+{:.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/english_vietnamese_maltese_model_en_5.5.0_3.0_1725795264051.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_vietnamese_maltese_model_en_5.5.0_3.0_1725795264051.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("english_vietnamese_maltese_model","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("english_vietnamese_maltese_model","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|english_vietnamese_maltese_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|474.6 MB|
+
+## References
+
+https://huggingface.co/haotieu/en-vi-mt-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-esci_mpnet_crossencoder_en.md b/docs/_posts/ahmedlone127/2024-09-08-esci_mpnet_crossencoder_en.md
new file mode 100644
index 00000000000000..ae0c4cb21a6c9a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-esci_mpnet_crossencoder_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English esci_mpnet_crossencoder MPNetEmbeddings from spacemanidol
+author: John Snow Labs
+name: esci_mpnet_crossencoder
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`esci_mpnet_crossencoder` is a English model originally trained by spacemanidol.
+
+{:.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/esci_mpnet_crossencoder_en_5.5.0_3.0_1725817263960.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esci_mpnet_crossencoder_en_5.5.0_3.0_1725817263960.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("esci_mpnet_crossencoder","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("esci_mpnet_crossencoder","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|esci_mpnet_crossencoder|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/spacemanidol/esci-mpnet-crossencoder
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-esg_bert_cnn_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-esg_bert_cnn_pipeline_en.md
new file mode 100644
index 00000000000000..68eed6565dbfaa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-esg_bert_cnn_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English esg_bert_cnn_pipeline pipeline BertForSequenceClassification from FaycalBk
+author: John Snow Labs
+name: esg_bert_cnn_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`esg_bert_cnn_pipeline` is a English model originally trained by FaycalBk.
+
+{:.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/esg_bert_cnn_pipeline_en_5.5.0_3.0_1725839205326.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esg_bert_cnn_pipeline_en_5.5.0_3.0_1725839205326.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
+
+pipeline = PretrainedPipeline("esg_bert_cnn_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("esg_bert_cnn_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|esg_bert_cnn_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.8 MB|
+
+## References
+
+https://huggingface.co/FaycalBk/ESG-bert-cnn
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-essai_en.md b/docs/_posts/ahmedlone127/2024-09-08-essai_en.md
new file mode 100644
index 00000000000000..9cdc92745efdc9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-essai_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English essai BertForSequenceClassification from diegovelilla
+author: John Snow Labs
+name: essai
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`essai` is a English model originally trained by diegovelilla.
+
+{:.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/essai_en_5.5.0_3.0_1725839527740.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/essai_en_5.5.0_3.0_1725839527740.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("essai","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("essai", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|essai|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/diegovelilla/EssAI
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-eth_setfit_multilabel_model_en.md b/docs/_posts/ahmedlone127/2024-09-08-eth_setfit_multilabel_model_en.md
new file mode 100644
index 00000000000000..195f689b2d742a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-eth_setfit_multilabel_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English eth_setfit_multilabel_model MPNetEmbeddings from physician-ethics-responsible-data-science
+author: John Snow Labs
+name: eth_setfit_multilabel_model
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`eth_setfit_multilabel_model` is a English model originally trained by physician-ethics-responsible-data-science.
+
+{:.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/eth_setfit_multilabel_model_en_5.5.0_3.0_1725816696742.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/eth_setfit_multilabel_model_en_5.5.0_3.0_1725816696742.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("eth_setfit_multilabel_model","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("eth_setfit_multilabel_model","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|eth_setfit_multilabel_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.0 MB|
+
+## References
+
+https://huggingface.co/physician-ethics-responsible-data-science/eth-setfit-multilabel-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-europarl_german_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-europarl_german_english_pipeline_en.md
new file mode 100644
index 00000000000000..d2b3ca354d6108
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-europarl_german_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English europarl_german_english_pipeline pipeline MarianTransformer from marsim0
+author: John Snow Labs
+name: europarl_german_english_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`europarl_german_english_pipeline` is a English model originally trained by marsim0.
+
+{:.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/europarl_german_english_pipeline_en_5.5.0_3.0_1725795227541.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/europarl_german_english_pipeline_en_5.5.0_3.0_1725795227541.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
+
+pipeline = PretrainedPipeline("europarl_german_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("europarl_german_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|europarl_german_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|500.0 MB|
+
+## References
+
+https://huggingface.co/marsim0/europarl-de-en
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-experiment_finetuned_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-experiment_finetuned_ner_pipeline_en.md
new file mode 100644
index 00000000000000..7c7e9069ec8306
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-experiment_finetuned_ner_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English experiment_finetuned_ner_pipeline pipeline DistilBertForTokenClassification from sophiestein
+author: John Snow Labs
+name: experiment_finetuned_ner_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`experiment_finetuned_ner_pipeline` is a English model originally trained by sophiestein.
+
+{:.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/experiment_finetuned_ner_pipeline_en_5.5.0_3.0_1725788386384.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/experiment_finetuned_ner_pipeline_en_5.5.0_3.0_1725788386384.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
+
+pipeline = PretrainedPipeline("experiment_finetuned_ner_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("experiment_finetuned_ner_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|experiment_finetuned_ner_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/sophiestein/experiment-finetuned-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-facets2_abl_num2_5_en.md b/docs/_posts/ahmedlone127/2024-09-08-facets2_abl_num2_5_en.md
new file mode 100644
index 00000000000000..0da38491d72eb0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-facets2_abl_num2_5_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English facets2_abl_num2_5 MPNetEmbeddings from ingeol
+author: John Snow Labs
+name: facets2_abl_num2_5
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`facets2_abl_num2_5` is a English model originally trained by ingeol.
+
+{:.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/facets2_abl_num2_5_en_5.5.0_3.0_1725769813755.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/facets2_abl_num2_5_en_5.5.0_3.0_1725769813755.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("facets2_abl_num2_5","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("facets2_abl_num2_5","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|facets2_abl_num2_5|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/ingeol/facets2_abl_num2_5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-facets2_re_10_10_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-facets2_re_10_10_pipeline_en.md
new file mode 100644
index 00000000000000..0d0b58fd4f5158
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-facets2_re_10_10_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English facets2_re_10_10_pipeline pipeline MPNetEmbeddings from ingeol
+author: John Snow Labs
+name: facets2_re_10_10_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`facets2_re_10_10_pipeline` is a English model originally trained by ingeol.
+
+{:.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/facets2_re_10_10_pipeline_en_5.5.0_3.0_1725816749485.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/facets2_re_10_10_pipeline_en_5.5.0_3.0_1725816749485.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
+
+pipeline = PretrainedPipeline("facets2_re_10_10_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("facets2_re_10_10_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|facets2_re_10_10_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/ingeol/facets2_re_10_10
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-facets_ep3_35_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-facets_ep3_35_pipeline_en.md
new file mode 100644
index 00000000000000..f1e00b6c471617
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-facets_ep3_35_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English facets_ep3_35_pipeline pipeline MPNetEmbeddings from ingeol
+author: John Snow Labs
+name: facets_ep3_35_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`facets_ep3_35_pipeline` is a English model originally trained by ingeol.
+
+{:.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/facets_ep3_35_pipeline_en_5.5.0_3.0_1725769759727.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/facets_ep3_35_pipeline_en_5.5.0_3.0_1725769759727.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
+
+pipeline = PretrainedPipeline("facets_ep3_35_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("facets_ep3_35_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|facets_ep3_35_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/ingeol/facets_ep3_35
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-facets_gpt_35_en.md b/docs/_posts/ahmedlone127/2024-09-08-facets_gpt_35_en.md
new file mode 100644
index 00000000000000..fec917e1d8810c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-facets_gpt_35_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English facets_gpt_35 MPNetEmbeddings from ingeol
+author: John Snow Labs
+name: facets_gpt_35
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`facets_gpt_35` is a English model originally trained by ingeol.
+
+{:.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/facets_gpt_35_en_5.5.0_3.0_1725769670643.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/facets_gpt_35_en_5.5.0_3.0_1725769670643.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("facets_gpt_35","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("facets_gpt_35","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|facets_gpt_35|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/ingeol/facets_gpt_35
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-fasee7v1_en.md b/docs/_posts/ahmedlone127/2024-09-08-fasee7v1_en.md
new file mode 100644
index 00000000000000..3843296d6485c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-fasee7v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English fasee7v1 MarianTransformer from Ahmed107
+author: John Snow Labs
+name: fasee7v1
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fasee7v1` is a English model originally trained by Ahmed107.
+
+{:.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/fasee7v1_en_5.5.0_3.0_1725831731478.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fasee7v1_en_5.5.0_3.0_1725831731478.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("fasee7v1","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("fasee7v1","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fasee7v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|527.9 MB|
+
+## References
+
+https://huggingface.co/Ahmed107/fasee7v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-fastai_deberta_v3_small_sigmorphon2022_v2_en.md b/docs/_posts/ahmedlone127/2024-09-08-fastai_deberta_v3_small_sigmorphon2022_v2_en.md
new file mode 100644
index 00000000000000..ca3485abc453c5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-fastai_deberta_v3_small_sigmorphon2022_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English fastai_deberta_v3_small_sigmorphon2022_v2 DeBertaForSequenceClassification from RazyDave
+author: John Snow Labs
+name: fastai_deberta_v3_small_sigmorphon2022_v2
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fastai_deberta_v3_small_sigmorphon2022_v2` is a English model originally trained by RazyDave.
+
+{:.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/fastai_deberta_v3_small_sigmorphon2022_v2_en_5.5.0_3.0_1725802852126.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fastai_deberta_v3_small_sigmorphon2022_v2_en_5.5.0_3.0_1725802852126.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("fastai_deberta_v3_small_sigmorphon2022_v2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("fastai_deberta_v3_small_sigmorphon2022_v2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fastai_deberta_v3_small_sigmorphon2022_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|498.6 MB|
+
+## References
+
+https://huggingface.co/RazyDave/FastAI-deberta-v3-small-SIGMORPHON2022-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-fastai_deberta_v3_small_sigmorphon2022_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-fastai_deberta_v3_small_sigmorphon2022_v2_pipeline_en.md
new file mode 100644
index 00000000000000..72d6cabbe26a79
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-fastai_deberta_v3_small_sigmorphon2022_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English fastai_deberta_v3_small_sigmorphon2022_v2_pipeline pipeline DeBertaForSequenceClassification from RazyDave
+author: John Snow Labs
+name: fastai_deberta_v3_small_sigmorphon2022_v2_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fastai_deberta_v3_small_sigmorphon2022_v2_pipeline` is a English model originally trained by RazyDave.
+
+{:.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/fastai_deberta_v3_small_sigmorphon2022_v2_pipeline_en_5.5.0_3.0_1725802878667.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fastai_deberta_v3_small_sigmorphon2022_v2_pipeline_en_5.5.0_3.0_1725802878667.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
+
+pipeline = PretrainedPipeline("fastai_deberta_v3_small_sigmorphon2022_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fastai_deberta_v3_small_sigmorphon2022_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fastai_deberta_v3_small_sigmorphon2022_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|498.6 MB|
+
+## References
+
+https://huggingface.co/RazyDave/FastAI-deberta-v3-small-SIGMORPHON2022-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-final_32shots_twitter_skhead_train_5epoch_bad_en.md b/docs/_posts/ahmedlone127/2024-09-08-final_32shots_twitter_skhead_train_5epoch_bad_en.md
new file mode 100644
index 00000000000000..4c6c36cbc401a5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-final_32shots_twitter_skhead_train_5epoch_bad_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English final_32shots_twitter_skhead_train_5epoch_bad MPNetEmbeddings from Nhat1904
+author: John Snow Labs
+name: final_32shots_twitter_skhead_train_5epoch_bad
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`final_32shots_twitter_skhead_train_5epoch_bad` is a English model originally trained by Nhat1904.
+
+{:.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/final_32shots_twitter_skhead_train_5epoch_bad_en_5.5.0_3.0_1725769375882.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/final_32shots_twitter_skhead_train_5epoch_bad_en_5.5.0_3.0_1725769375882.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("final_32shots_twitter_skhead_train_5epoch_bad","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("final_32shots_twitter_skhead_train_5epoch_bad","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|final_32shots_twitter_skhead_train_5epoch_bad|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/Nhat1904/Final-32shots-Twitter-Skhead-Train-5epoch-bad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-finalmodel_setarehmohammadpour_en.md b/docs/_posts/ahmedlone127/2024-09-08-finalmodel_setarehmohammadpour_en.md
new file mode 100644
index 00000000000000..2df7fd25ce4574
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-finalmodel_setarehmohammadpour_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finalmodel_setarehmohammadpour DistilBertForSequenceClassification from SetarehMohammadpour
+author: John Snow Labs
+name: finalmodel_setarehmohammadpour
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finalmodel_setarehmohammadpour` is a English model originally trained by SetarehMohammadpour.
+
+{:.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/finalmodel_setarehmohammadpour_en_5.5.0_3.0_1725775054582.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finalmodel_setarehmohammadpour_en_5.5.0_3.0_1725775054582.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finalmodel_setarehmohammadpour","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finalmodel_setarehmohammadpour", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finalmodel_setarehmohammadpour|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|250.9 MB|
+
+## References
+
+https://huggingface.co/SetarehMohammadpour/finalmodel
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-fine_tuned_marianmt_english_vietnamese_en.md b/docs/_posts/ahmedlone127/2024-09-08-fine_tuned_marianmt_english_vietnamese_en.md
new file mode 100644
index 00000000000000..f5d8552cb9b258
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-fine_tuned_marianmt_english_vietnamese_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English fine_tuned_marianmt_english_vietnamese MarianTransformer from nwdy
+author: John Snow Labs
+name: fine_tuned_marianmt_english_vietnamese
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_marianmt_english_vietnamese` is a English model originally trained by nwdy.
+
+{:.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/fine_tuned_marianmt_english_vietnamese_en_5.5.0_3.0_1725831541567.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_marianmt_english_vietnamese_en_5.5.0_3.0_1725831541567.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("fine_tuned_marianmt_english_vietnamese","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("fine_tuned_marianmt_english_vietnamese","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_marianmt_english_vietnamese|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|474.5 MB|
+
+## References
+
+https://huggingface.co/nwdy/fine-tuned-marianmt-en-vi
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-fine_tuned_marianmt_english_vietnamese_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-fine_tuned_marianmt_english_vietnamese_pipeline_en.md
new file mode 100644
index 00000000000000..043a799480f492
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-fine_tuned_marianmt_english_vietnamese_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English fine_tuned_marianmt_english_vietnamese_pipeline pipeline MarianTransformer from nwdy
+author: John Snow Labs
+name: fine_tuned_marianmt_english_vietnamese_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_marianmt_english_vietnamese_pipeline` is a English model originally trained by nwdy.
+
+{:.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/fine_tuned_marianmt_english_vietnamese_pipeline_en_5.5.0_3.0_1725831565178.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_marianmt_english_vietnamese_pipeline_en_5.5.0_3.0_1725831565178.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
+
+pipeline = PretrainedPipeline("fine_tuned_marianmt_english_vietnamese_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_marianmt_english_vietnamese_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_marianmt_english_vietnamese_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|475.1 MB|
+
+## References
+
+https://huggingface.co/nwdy/fine-tuned-marianmt-en-vi
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-finetuned2_ivanzhuo99_en.md b/docs/_posts/ahmedlone127/2024-09-08-finetuned2_ivanzhuo99_en.md
new file mode 100644
index 00000000000000..141a4b7820f762
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-finetuned2_ivanzhuo99_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English finetuned2_ivanzhuo99 DistilBertForQuestionAnswering from ivanzhuo99
+author: John Snow Labs
+name: finetuned2_ivanzhuo99
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned2_ivanzhuo99` is a English model originally trained by ivanzhuo99.
+
+{:.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/finetuned2_ivanzhuo99_en_5.5.0_3.0_1725818110432.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned2_ivanzhuo99_en_5.5.0_3.0_1725818110432.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("finetuned2_ivanzhuo99","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("finetuned2_ivanzhuo99", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned2_ivanzhuo99|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/ivanzhuo99/finetuned2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-finetuned2_ivanzhuo99_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-finetuned2_ivanzhuo99_pipeline_en.md
new file mode 100644
index 00000000000000..752f36b18509f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-finetuned2_ivanzhuo99_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English finetuned2_ivanzhuo99_pipeline pipeline DistilBertForQuestionAnswering from ivanzhuo99
+author: John Snow Labs
+name: finetuned2_ivanzhuo99_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned2_ivanzhuo99_pipeline` is a English model originally trained by ivanzhuo99.
+
+{:.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/finetuned2_ivanzhuo99_pipeline_en_5.5.0_3.0_1725818124182.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned2_ivanzhuo99_pipeline_en_5.5.0_3.0_1725818124182.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
+
+pipeline = PretrainedPipeline("finetuned2_ivanzhuo99_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned2_ivanzhuo99_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned2_ivanzhuo99_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/ivanzhuo99/finetuned2
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-finetuned_customer_intent_distilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-finetuned_customer_intent_distilbert_pipeline_en.md
new file mode 100644
index 00000000000000..0fbf77e64cdfe2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-finetuned_customer_intent_distilbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuned_customer_intent_distilbert_pipeline pipeline DistilBertForSequenceClassification from MKB44
+author: John Snow Labs
+name: finetuned_customer_intent_distilbert_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_customer_intent_distilbert_pipeline` is a English model originally trained by MKB44.
+
+{:.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/finetuned_customer_intent_distilbert_pipeline_en_5.5.0_3.0_1725764686881.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_customer_intent_distilbert_pipeline_en_5.5.0_3.0_1725764686881.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
+
+pipeline = PretrainedPipeline("finetuned_customer_intent_distilbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_customer_intent_distilbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_customer_intent_distilbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|246.1 MB|
+
+## References
+
+https://huggingface.co/MKB44/finetuned-customer-intent-distilbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-finetuned_deberta_isear_4_en.md b/docs/_posts/ahmedlone127/2024-09-08-finetuned_deberta_isear_4_en.md
new file mode 100644
index 00000000000000..4ba08a94a0b8c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-finetuned_deberta_isear_4_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuned_deberta_isear_4 DeBertaForSequenceClassification from UO282436
+author: John Snow Labs
+name: finetuned_deberta_isear_4
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_deberta_isear_4` is a English model originally trained by UO282436.
+
+{:.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/finetuned_deberta_isear_4_en_5.5.0_3.0_1725812418133.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_deberta_isear_4_en_5.5.0_3.0_1725812418133.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("finetuned_deberta_isear_4","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("finetuned_deberta_isear_4", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_deberta_isear_4|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|563.1 MB|
+
+## References
+
+https://huggingface.co/UO282436/finetuned-deberta-ISEAR_4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-finetuned_deberta_isear_4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-finetuned_deberta_isear_4_pipeline_en.md
new file mode 100644
index 00000000000000..0c07e6edf77b4c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-finetuned_deberta_isear_4_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuned_deberta_isear_4_pipeline pipeline DeBertaForSequenceClassification from UO282436
+author: John Snow Labs
+name: finetuned_deberta_isear_4_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_deberta_isear_4_pipeline` is a English model originally trained by UO282436.
+
+{:.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/finetuned_deberta_isear_4_pipeline_en_5.5.0_3.0_1725812503074.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_deberta_isear_4_pipeline_en_5.5.0_3.0_1725812503074.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
+
+pipeline = PretrainedPipeline("finetuned_deberta_isear_4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_deberta_isear_4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_deberta_isear_4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|563.1 MB|
+
+## References
+
+https://huggingface.co/UO282436/finetuned-deberta-ISEAR_4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-finetuned_iitp_pdt_review_additionalpretrained_indic_bert_en.md b/docs/_posts/ahmedlone127/2024-09-08-finetuned_iitp_pdt_review_additionalpretrained_indic_bert_en.md
new file mode 100644
index 00000000000000..ea5fc428dbc731
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-finetuned_iitp_pdt_review_additionalpretrained_indic_bert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuned_iitp_pdt_review_additionalpretrained_indic_bert AlbertForSequenceClassification from aditeyabaral
+author: John Snow Labs
+name: finetuned_iitp_pdt_review_additionalpretrained_indic_bert
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_iitp_pdt_review_additionalpretrained_indic_bert` is a English model originally trained by aditeyabaral.
+
+{:.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/finetuned_iitp_pdt_review_additionalpretrained_indic_bert_en_5.5.0_3.0_1725767012957.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_iitp_pdt_review_additionalpretrained_indic_bert_en_5.5.0_3.0_1725767012957.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("finetuned_iitp_pdt_review_additionalpretrained_indic_bert","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("finetuned_iitp_pdt_review_additionalpretrained_indic_bert", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_iitp_pdt_review_additionalpretrained_indic_bert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|127.8 MB|
+
+## References
+
+https://huggingface.co/aditeyabaral/finetuned-iitp_pdt_review-additionalpretrained-indic-bert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-finetuned_iitp_pdt_review_additionalpretrained_indic_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-finetuned_iitp_pdt_review_additionalpretrained_indic_bert_pipeline_en.md
new file mode 100644
index 00000000000000..dcb562e1b919a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-finetuned_iitp_pdt_review_additionalpretrained_indic_bert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuned_iitp_pdt_review_additionalpretrained_indic_bert_pipeline pipeline AlbertForSequenceClassification from aditeyabaral
+author: John Snow Labs
+name: finetuned_iitp_pdt_review_additionalpretrained_indic_bert_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_iitp_pdt_review_additionalpretrained_indic_bert_pipeline` is a English model originally trained by aditeyabaral.
+
+{:.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/finetuned_iitp_pdt_review_additionalpretrained_indic_bert_pipeline_en_5.5.0_3.0_1725767019188.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_iitp_pdt_review_additionalpretrained_indic_bert_pipeline_en_5.5.0_3.0_1725767019188.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
+
+pipeline = PretrainedPipeline("finetuned_iitp_pdt_review_additionalpretrained_indic_bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_iitp_pdt_review_additionalpretrained_indic_bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_iitp_pdt_review_additionalpretrained_indic_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|127.8 MB|
+
+## References
+
+https://huggingface.co/aditeyabaral/finetuned-iitp_pdt_review-additionalpretrained-indic-bert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- AlbertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-finetuned_squad_v2_en.md b/docs/_posts/ahmedlone127/2024-09-08-finetuned_squad_v2_en.md
new file mode 100644
index 00000000000000..24397fc957f9db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-finetuned_squad_v2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English finetuned_squad_v2 DistilBertForQuestionAnswering from Andru
+author: John Snow Labs
+name: finetuned_squad_v2
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_squad_v2` is a English model originally trained by Andru.
+
+{:.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/finetuned_squad_v2_en_5.5.0_3.0_1725818351602.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_squad_v2_en_5.5.0_3.0_1725818351602.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("finetuned_squad_v2","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("finetuned_squad_v2", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_squad_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Andru/finetuned-squad_v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-finetuned_squad_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-finetuned_squad_v2_pipeline_en.md
new file mode 100644
index 00000000000000..ab29db79dd834c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-finetuned_squad_v2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English finetuned_squad_v2_pipeline pipeline DistilBertForQuestionAnswering from Andru
+author: John Snow Labs
+name: finetuned_squad_v2_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_squad_v2_pipeline` is a English model originally trained by Andru.
+
+{:.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/finetuned_squad_v2_pipeline_en_5.5.0_3.0_1725818364196.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_squad_v2_pipeline_en_5.5.0_3.0_1725818364196.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
+
+pipeline = PretrainedPipeline("finetuned_squad_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_squad_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_squad_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Andru/finetuned-squad_v2
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-finetuning_bm25_small_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-finetuning_bm25_small_pipeline_en.md
new file mode 100644
index 00000000000000..f100230a171266
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-finetuning_bm25_small_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English finetuning_bm25_small_pipeline pipeline MPNetEmbeddings from jhsmith
+author: John Snow Labs
+name: finetuning_bm25_small_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_bm25_small_pipeline` is a English model originally trained by jhsmith.
+
+{:.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/finetuning_bm25_small_pipeline_en_5.5.0_3.0_1725769523359.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_bm25_small_pipeline_en_5.5.0_3.0_1725769523359.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
+
+pipeline = PretrainedPipeline("finetuning_bm25_small_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_bm25_small_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_bm25_small_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/jhsmith/finetuning_bm25_small
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-finetuning_sentiment_model_3000_samples_nico10hahn17_en.md b/docs/_posts/ahmedlone127/2024-09-08-finetuning_sentiment_model_3000_samples_nico10hahn17_en.md
new file mode 100644
index 00000000000000..4a181bfbe635d2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-finetuning_sentiment_model_3000_samples_nico10hahn17_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_nico10hahn17 DistilBertForSequenceClassification from Nico10Hahn17
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_nico10hahn17
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_nico10hahn17` is a English model originally trained by Nico10Hahn17.
+
+{:.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/finetuning_sentiment_model_3000_samples_nico10hahn17_en_5.5.0_3.0_1725775251948.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_nico10hahn17_en_5.5.0_3.0_1725775251948.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_nico10hahn17","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_nico10hahn17", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_nico10hahn17|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Nico10Hahn17/finetuning-sentiment-model-3000-samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-flipped_1_en.md b/docs/_posts/ahmedlone127/2024-09-08-flipped_1_en.md
new file mode 100644
index 00000000000000..7381e2f78cd2c2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-flipped_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English flipped_1 XlmRoBertaForTokenClassification from grace-pro
+author: John Snow Labs
+name: flipped_1
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flipped_1` is a English model originally trained by grace-pro.
+
+{:.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/flipped_1_en_5.5.0_3.0_1725784041122.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flipped_1_en_5.5.0_3.0_1725784041122.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("flipped_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("flipped_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flipped_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/grace-pro/flipped_1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-flipped_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-flipped_1_pipeline_en.md
new file mode 100644
index 00000000000000..71792b371978e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-flipped_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English flipped_1_pipeline pipeline XlmRoBertaForTokenClassification from grace-pro
+author: John Snow Labs
+name: flipped_1_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flipped_1_pipeline` is a English model originally trained by grace-pro.
+
+{:.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/flipped_1_pipeline_en_5.5.0_3.0_1725784089034.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flipped_1_pipeline_en_5.5.0_3.0_1725784089034.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
+
+pipeline = PretrainedPipeline("flipped_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("flipped_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|flipped_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/grace-pro/flipped_1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-frabert_distilbert_base_uncased_51086_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-frabert_distilbert_base_uncased_51086_1_pipeline_en.md
new file mode 100644
index 00000000000000..a5c39780ded3e2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-frabert_distilbert_base_uncased_51086_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English frabert_distilbert_base_uncased_51086_1_pipeline pipeline DistilBertForSequenceClassification from Francesco0101
+author: John Snow Labs
+name: frabert_distilbert_base_uncased_51086_1_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`frabert_distilbert_base_uncased_51086_1_pipeline` is a English model originally trained by Francesco0101.
+
+{:.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/frabert_distilbert_base_uncased_51086_1_pipeline_en_5.5.0_3.0_1725808458803.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/frabert_distilbert_base_uncased_51086_1_pipeline_en_5.5.0_3.0_1725808458803.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
+
+pipeline = PretrainedPipeline("frabert_distilbert_base_uncased_51086_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("frabert_distilbert_base_uncased_51086_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|frabert_distilbert_base_uncased_51086_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Francesco0101/FRABERT-distilbert-base-uncased-51086-1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-from_classifier_v0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-from_classifier_v0_pipeline_en.md
new file mode 100644
index 00000000000000..0daf55562f8f3a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-from_classifier_v0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English from_classifier_v0_pipeline pipeline MPNetEmbeddings from futuredatascience
+author: John Snow Labs
+name: from_classifier_v0_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`from_classifier_v0_pipeline` is a English model originally trained by futuredatascience.
+
+{:.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/from_classifier_v0_pipeline_en_5.5.0_3.0_1725769915456.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/from_classifier_v0_pipeline_en_5.5.0_3.0_1725769915456.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
+
+pipeline = PretrainedPipeline("from_classifier_v0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("from_classifier_v0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|from_classifier_v0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/futuredatascience/from-classifier-v0
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-full_review_clf_en.md b/docs/_posts/ahmedlone127/2024-09-08-full_review_clf_en.md
new file mode 100644
index 00000000000000..06f320eeb8dec6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-full_review_clf_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English full_review_clf RoBertaForSequenceClassification from justina
+author: John Snow Labs
+name: full_review_clf
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`full_review_clf` is a English model originally trained by justina.
+
+{:.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/full_review_clf_en_5.5.0_3.0_1725820535771.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/full_review_clf_en_5.5.0_3.0_1725820535771.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("full_review_clf","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("full_review_clf", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|full_review_clf|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|468.3 MB|
+
+## References
+
+https://huggingface.co/justina/full-review-clf
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-full_review_clf_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-full_review_clf_pipeline_en.md
new file mode 100644
index 00000000000000..24fd09b778e05b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-full_review_clf_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English full_review_clf_pipeline pipeline RoBertaForSequenceClassification from justina
+author: John Snow Labs
+name: full_review_clf_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`full_review_clf_pipeline` is a English model originally trained by justina.
+
+{:.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/full_review_clf_pipeline_en_5.5.0_3.0_1725820559468.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/full_review_clf_pipeline_en_5.5.0_3.0_1725820559468.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
+
+pipeline = PretrainedPipeline("full_review_clf_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("full_review_clf_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|full_review_clf_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.3 MB|
+
+## References
+
+https://huggingface.co/justina/full-review-clf
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-g_sciedbert_de.md b/docs/_posts/ahmedlone127/2024-09-08-g_sciedbert_de.md
new file mode 100644
index 00000000000000..c3e9b23f33f12f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-g_sciedbert_de.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: German g_sciedbert BertForSequenceClassification from ai4stem-uga
+author: John Snow Labs
+name: g_sciedbert
+date: 2024-09-08
+tags: [de, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`g_sciedbert` is a German model originally trained by ai4stem-uga.
+
+{:.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/g_sciedbert_de_5.5.0_3.0_1725819455205.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/g_sciedbert_de_5.5.0_3.0_1725819455205.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("g_sciedbert","de") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("g_sciedbert", "de")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|g_sciedbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|de|
+|Size:|409.1 MB|
+
+## References
+
+https://huggingface.co/ai4stem-uga/G-SciEdBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-georgian_corpus_model_en.md b/docs/_posts/ahmedlone127/2024-09-08-georgian_corpus_model_en.md
new file mode 100644
index 00000000000000..c9bb0f3d18529c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-georgian_corpus_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English georgian_corpus_model BertEmbeddings from RichNachos
+author: John Snow Labs
+name: georgian_corpus_model
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`georgian_corpus_model` is a English model originally trained by RichNachos.
+
+{:.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/georgian_corpus_model_en_5.5.0_3.0_1725792727717.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/georgian_corpus_model_en_5.5.0_3.0_1725792727717.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("georgian_corpus_model","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("georgian_corpus_model","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|georgian_corpus_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|107.1 MB|
+
+## References
+
+https://huggingface.co/RichNachos/georgian-corpus-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-germanfinbert_sardinian_sentiment_de.md b/docs/_posts/ahmedlone127/2024-09-08-germanfinbert_sardinian_sentiment_de.md
new file mode 100644
index 00000000000000..8d65624cfc2e53
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-germanfinbert_sardinian_sentiment_de.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: German germanfinbert_sardinian_sentiment BertForSequenceClassification from scherrmann
+author: John Snow Labs
+name: germanfinbert_sardinian_sentiment
+date: 2024-09-08
+tags: [de, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`germanfinbert_sardinian_sentiment` is a German model originally trained by scherrmann.
+
+{:.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/germanfinbert_sardinian_sentiment_de_5.5.0_3.0_1725826045810.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/germanfinbert_sardinian_sentiment_de_5.5.0_3.0_1725826045810.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("germanfinbert_sardinian_sentiment","de") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("germanfinbert_sardinian_sentiment", "de")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|germanfinbert_sardinian_sentiment|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|de|
+|Size:|408.1 MB|
+
+## References
+
+https://huggingface.co/scherrmann/GermanFinBert_SC_Sentiment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-germanfinbert_sardinian_sentiment_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-08-germanfinbert_sardinian_sentiment_pipeline_de.md
new file mode 100644
index 00000000000000..3877a07a11fc62
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-germanfinbert_sardinian_sentiment_pipeline_de.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: German germanfinbert_sardinian_sentiment_pipeline pipeline BertForSequenceClassification from scherrmann
+author: John Snow Labs
+name: germanfinbert_sardinian_sentiment_pipeline
+date: 2024-09-08
+tags: [de, open_source, pipeline, onnx]
+task: Text Classification
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`germanfinbert_sardinian_sentiment_pipeline` is a German model originally trained by scherrmann.
+
+{:.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/germanfinbert_sardinian_sentiment_pipeline_de_5.5.0_3.0_1725826065586.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/germanfinbert_sardinian_sentiment_pipeline_de_5.5.0_3.0_1725826065586.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
+
+pipeline = PretrainedPipeline("germanfinbert_sardinian_sentiment_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("germanfinbert_sardinian_sentiment_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|germanfinbert_sardinian_sentiment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|408.1 MB|
+
+## References
+
+https://huggingface.co/scherrmann/GermanFinBert_SC_Sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-gitlab_marathi_marh_analysis_default_model_samaksh_khatri_en.md b/docs/_posts/ahmedlone127/2024-09-08-gitlab_marathi_marh_analysis_default_model_samaksh_khatri_en.md
new file mode 100644
index 00000000000000..f3a91956d0536a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-gitlab_marathi_marh_analysis_default_model_samaksh_khatri_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English gitlab_marathi_marh_analysis_default_model_samaksh_khatri DistilBertForSequenceClassification from samaksh-khatri
+author: John Snow Labs
+name: gitlab_marathi_marh_analysis_default_model_samaksh_khatri
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gitlab_marathi_marh_analysis_default_model_samaksh_khatri` is a English model originally trained by samaksh-khatri.
+
+{:.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/gitlab_marathi_marh_analysis_default_model_samaksh_khatri_en_5.5.0_3.0_1725764566768.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gitlab_marathi_marh_analysis_default_model_samaksh_khatri_en_5.5.0_3.0_1725764566768.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("gitlab_marathi_marh_analysis_default_model_samaksh_khatri","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("gitlab_marathi_marh_analysis_default_model_samaksh_khatri", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gitlab_marathi_marh_analysis_default_model_samaksh_khatri|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.4 MB|
+
+## References
+
+https://huggingface.co/samaksh-khatri/gitlab-mr-analysis-default-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-gliner_haystack_en.md b/docs/_posts/ahmedlone127/2024-09-08-gliner_haystack_en.md
new file mode 100644
index 00000000000000..7bbe8a55720dca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-gliner_haystack_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English gliner_haystack BertForTokenClassification from NORMA-DEV
+author: John Snow Labs
+name: gliner_haystack
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gliner_haystack` is a English model originally trained by NORMA-DEV.
+
+{:.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/gliner_haystack_en_5.5.0_3.0_1725822383127.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gliner_haystack_en_5.5.0_3.0_1725822383127.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("gliner_haystack","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("gliner_haystack", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gliner_haystack|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/NORMA-DEV/Gliner_haystack
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-gliner_haystack_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-gliner_haystack_pipeline_en.md
new file mode 100644
index 00000000000000..d3d5ffcc9d5257
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-gliner_haystack_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English gliner_haystack_pipeline pipeline BertForTokenClassification from NORMA-DEV
+author: John Snow Labs
+name: gliner_haystack_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gliner_haystack_pipeline` is a English model originally trained by NORMA-DEV.
+
+{:.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/gliner_haystack_pipeline_en_5.5.0_3.0_1725822403748.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gliner_haystack_pipeline_en_5.5.0_3.0_1725822403748.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
+
+pipeline = PretrainedPipeline("gliner_haystack_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gliner_haystack_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gliner_haystack_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/NORMA-DEV/Gliner_haystack
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-hate_hate_balance_random0_seed2_twitter_roberta_base_2019_90m_en.md b/docs/_posts/ahmedlone127/2024-09-08-hate_hate_balance_random0_seed2_twitter_roberta_base_2019_90m_en.md
new file mode 100644
index 00000000000000..a450373e2fbab5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-hate_hate_balance_random0_seed2_twitter_roberta_base_2019_90m_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English hate_hate_balance_random0_seed2_twitter_roberta_base_2019_90m RoBertaForSequenceClassification from tweettemposhift
+author: John Snow Labs
+name: hate_hate_balance_random0_seed2_twitter_roberta_base_2019_90m
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hate_hate_balance_random0_seed2_twitter_roberta_base_2019_90m` is a English model originally trained by tweettemposhift.
+
+{:.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/hate_hate_balance_random0_seed2_twitter_roberta_base_2019_90m_en_5.5.0_3.0_1725830410801.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hate_hate_balance_random0_seed2_twitter_roberta_base_2019_90m_en_5.5.0_3.0_1725830410801.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("hate_hate_balance_random0_seed2_twitter_roberta_base_2019_90m","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("hate_hate_balance_random0_seed2_twitter_roberta_base_2019_90m", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hate_hate_balance_random0_seed2_twitter_roberta_base_2019_90m|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|468.3 MB|
+
+## References
+
+https://huggingface.co/tweettemposhift/hate-hate_balance_random0_seed2-twitter-roberta-base-2019-90m
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-hate_hate_balance_random0_seed2_twitter_roberta_base_2019_90m_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-hate_hate_balance_random0_seed2_twitter_roberta_base_2019_90m_pipeline_en.md
new file mode 100644
index 00000000000000..d43f822f2c1632
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-hate_hate_balance_random0_seed2_twitter_roberta_base_2019_90m_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English hate_hate_balance_random0_seed2_twitter_roberta_base_2019_90m_pipeline pipeline RoBertaForSequenceClassification from tweettemposhift
+author: John Snow Labs
+name: hate_hate_balance_random0_seed2_twitter_roberta_base_2019_90m_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hate_hate_balance_random0_seed2_twitter_roberta_base_2019_90m_pipeline` is a English model originally trained by tweettemposhift.
+
+{:.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/hate_hate_balance_random0_seed2_twitter_roberta_base_2019_90m_pipeline_en_5.5.0_3.0_1725830434377.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hate_hate_balance_random0_seed2_twitter_roberta_base_2019_90m_pipeline_en_5.5.0_3.0_1725830434377.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
+
+pipeline = PretrainedPipeline("hate_hate_balance_random0_seed2_twitter_roberta_base_2019_90m_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hate_hate_balance_random0_seed2_twitter_roberta_base_2019_90m_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hate_hate_balance_random0_seed2_twitter_roberta_base_2019_90m_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.3 MB|
+
+## References
+
+https://huggingface.co/tweettemposhift/hate-hate_balance_random0_seed2-twitter-roberta-base-2019-90m
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-helsinki_danish_swedish_v11_en.md b/docs/_posts/ahmedlone127/2024-09-08-helsinki_danish_swedish_v11_en.md
new file mode 100644
index 00000000000000..d7bcfa6739a938
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-helsinki_danish_swedish_v11_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English helsinki_danish_swedish_v11 MarianTransformer from Danieljacobsen
+author: John Snow Labs
+name: helsinki_danish_swedish_v11
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`helsinki_danish_swedish_v11` is a English model originally trained by Danieljacobsen.
+
+{:.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/helsinki_danish_swedish_v11_en_5.5.0_3.0_1725795199698.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/helsinki_danish_swedish_v11_en_5.5.0_3.0_1725795199698.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("helsinki_danish_swedish_v11","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("helsinki_danish_swedish_v11","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|helsinki_danish_swedish_v11|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|496.8 MB|
+
+## References
+
+https://huggingface.co/Danieljacobsen/Helsinki-DA-SV-v11
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-helsinki_danish_swedish_v11_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-helsinki_danish_swedish_v11_pipeline_en.md
new file mode 100644
index 00000000000000..0d9efda3cd2954
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-helsinki_danish_swedish_v11_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English helsinki_danish_swedish_v11_pipeline pipeline MarianTransformer from Danieljacobsen
+author: John Snow Labs
+name: helsinki_danish_swedish_v11_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`helsinki_danish_swedish_v11_pipeline` is a English model originally trained by Danieljacobsen.
+
+{:.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/helsinki_danish_swedish_v11_pipeline_en_5.5.0_3.0_1725795227807.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/helsinki_danish_swedish_v11_pipeline_en_5.5.0_3.0_1725795227807.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
+
+pipeline = PretrainedPipeline("helsinki_danish_swedish_v11_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("helsinki_danish_swedish_v11_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|helsinki_danish_swedish_v11_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|497.4 MB|
+
+## References
+
+https://huggingface.co/Danieljacobsen/Helsinki-DA-SV-v11
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-helsinki_danish_swedish_v14_en.md b/docs/_posts/ahmedlone127/2024-09-08-helsinki_danish_swedish_v14_en.md
new file mode 100644
index 00000000000000..cf3300fcba30f9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-helsinki_danish_swedish_v14_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English helsinki_danish_swedish_v14 MarianTransformer from Danieljacobsen
+author: John Snow Labs
+name: helsinki_danish_swedish_v14
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`helsinki_danish_swedish_v14` is a English model originally trained by Danieljacobsen.
+
+{:.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/helsinki_danish_swedish_v14_en_5.5.0_3.0_1725795705718.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/helsinki_danish_swedish_v14_en_5.5.0_3.0_1725795705718.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("helsinki_danish_swedish_v14","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("helsinki_danish_swedish_v14","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|helsinki_danish_swedish_v14|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|496.8 MB|
+
+## References
+
+https://huggingface.co/Danieljacobsen/Helsinki-DA-SV-v14
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-helsinki_english_spanish_fine_tune_opus100_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-helsinki_english_spanish_fine_tune_opus100_pipeline_en.md
new file mode 100644
index 00000000000000..218781f1063678
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-helsinki_english_spanish_fine_tune_opus100_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English helsinki_english_spanish_fine_tune_opus100_pipeline pipeline MarianTransformer from beanslmao
+author: John Snow Labs
+name: helsinki_english_spanish_fine_tune_opus100_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`helsinki_english_spanish_fine_tune_opus100_pipeline` is a English model originally trained by beanslmao.
+
+{:.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/helsinki_english_spanish_fine_tune_opus100_pipeline_en_5.5.0_3.0_1725839873061.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/helsinki_english_spanish_fine_tune_opus100_pipeline_en_5.5.0_3.0_1725839873061.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
+
+pipeline = PretrainedPipeline("helsinki_english_spanish_fine_tune_opus100_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("helsinki_english_spanish_fine_tune_opus100_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|helsinki_english_spanish_fine_tune_opus100_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|540.4 MB|
+
+## References
+
+https://huggingface.co/beanslmao/helsinki-en-es-fine-tune-opus100
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-helsinki_nlp_opus_maltese_english_multiple_languages_opus100_accelerate_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-helsinki_nlp_opus_maltese_english_multiple_languages_opus100_accelerate_pipeline_en.md
new file mode 100644
index 00000000000000..5ce0a10bff7f06
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-helsinki_nlp_opus_maltese_english_multiple_languages_opus100_accelerate_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English helsinki_nlp_opus_maltese_english_multiple_languages_opus100_accelerate_pipeline pipeline MarianTransformer from MikolajDeja
+author: John Snow Labs
+name: helsinki_nlp_opus_maltese_english_multiple_languages_opus100_accelerate_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`helsinki_nlp_opus_maltese_english_multiple_languages_opus100_accelerate_pipeline` is a English model originally trained by MikolajDeja.
+
+{:.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/helsinki_nlp_opus_maltese_english_multiple_languages_opus100_accelerate_pipeline_en_5.5.0_3.0_1725765536823.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/helsinki_nlp_opus_maltese_english_multiple_languages_opus100_accelerate_pipeline_en_5.5.0_3.0_1725765536823.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
+
+pipeline = PretrainedPipeline("helsinki_nlp_opus_maltese_english_multiple_languages_opus100_accelerate_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("helsinki_nlp_opus_maltese_english_multiple_languages_opus100_accelerate_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|helsinki_nlp_opus_maltese_english_multiple_languages_opus100_accelerate_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|527.3 MB|
+
+## References
+
+https://huggingface.co/MikolajDeja/Helsinki-NLP-opus-mt-en-mul-opus100-accelerate
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-hindi_bert_v2_pipeline_hi.md b/docs/_posts/ahmedlone127/2024-09-08-hindi_bert_v2_pipeline_hi.md
new file mode 100644
index 00000000000000..f0814cf5af72ea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-hindi_bert_v2_pipeline_hi.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Hindi hindi_bert_v2_pipeline pipeline BertForSequenceClassification from arnabmukhopadhyay
+author: John Snow Labs
+name: hindi_bert_v2_pipeline
+date: 2024-09-08
+tags: [hi, open_source, pipeline, onnx]
+task: Text Classification
+language: hi
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hindi_bert_v2_pipeline` is a Hindi model originally trained by arnabmukhopadhyay.
+
+{:.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/hindi_bert_v2_pipeline_hi_5.5.0_3.0_1725826216266.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hindi_bert_v2_pipeline_hi_5.5.0_3.0_1725826216266.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
+
+pipeline = PretrainedPipeline("hindi_bert_v2_pipeline", lang = "hi")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hindi_bert_v2_pipeline", lang = "hi")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hindi_bert_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|hi|
+|Size:|892.9 MB|
+
+## References
+
+https://huggingface.co/arnabmukhopadhyay/Hindi-bert-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-huggingfacetextclassification_en.md b/docs/_posts/ahmedlone127/2024-09-08-huggingfacetextclassification_en.md
new file mode 100644
index 00000000000000..e712f94ef6e110
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-huggingfacetextclassification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English huggingfacetextclassification DistilBertForSequenceClassification from NandaKr
+author: John Snow Labs
+name: huggingfacetextclassification
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`huggingfacetextclassification` is a English model originally trained by NandaKr.
+
+{:.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/huggingfacetextclassification_en_5.5.0_3.0_1725775153364.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/huggingfacetextclassification_en_5.5.0_3.0_1725775153364.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("huggingfacetextclassification","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("huggingfacetextclassification", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|huggingfacetextclassification|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/NandaKr/HuggingFaceTextClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-ikitracs_mitigation_en.md b/docs/_posts/ahmedlone127/2024-09-08-ikitracs_mitigation_en.md
new file mode 100644
index 00000000000000..40bf96f7c67b81
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-ikitracs_mitigation_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English ikitracs_mitigation MPNetEmbeddings from ilaria-oneofftech
+author: John Snow Labs
+name: ikitracs_mitigation
+date: 2024-09-08
+tags: [mpnet, en, open_source, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetForSequenceClassification
+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.`ikitracs_mitigation` is a English model originally trained by ilaria-oneofftech.
+
+## 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/ikitracs_mitigation_en_5.5.0_3.0_1725827043174.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ikitracs_mitigation_en_5.5.0_3.0_1725827043174.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("ikitracs_mitigation","en") \
+            .setInputCols(["documents"]) \
+            .setOutputCol("mpnet_embeddings")
+
+pipeline = Pipeline().setStages([document_assembler, embeddings])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("documents")
+    
+val embeddings = MPNetEmbeddings 
+    .pretrained("ikitracs_mitigation", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("mpnet_embeddings") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ikitracs_mitigation|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.6 MB|
+
+## References
+
+References
+
+https://huggingface.co/ilaria-oneofftech/ikitracs_mitigation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-ikitracs_mitigation_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-ikitracs_mitigation_pipeline_en.md
new file mode 100644
index 00000000000000..f24e8fdb195636
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-ikitracs_mitigation_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ikitracs_mitigation_pipeline pipeline MPNetForSequenceClassification from ilaria-oneofftech
+author: John Snow Labs
+name: ikitracs_mitigation_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ikitracs_mitigation_pipeline` is a English model originally trained by ilaria-oneofftech.
+
+{:.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/ikitracs_mitigation_pipeline_en_5.5.0_3.0_1725827062518.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ikitracs_mitigation_pipeline_en_5.5.0_3.0_1725827062518.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
+
+pipeline = PretrainedPipeline("ikitracs_mitigation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ikitracs_mitigation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ikitracs_mitigation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.6 MB|
+
+## References
+
+https://huggingface.co/ilaria-oneofftech/ikitracs_mitigation
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- MPNetForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-imdb_2_en.md b/docs/_posts/ahmedlone127/2024-09-08-imdb_2_en.md
new file mode 100644
index 00000000000000..272dc34e2edc88
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-imdb_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English imdb_2 DistilBertForSequenceClassification from draghicivlad
+author: John Snow Labs
+name: imdb_2
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`imdb_2` is a English model originally trained by draghicivlad.
+
+{:.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/imdb_2_en_5.5.0_3.0_1725775349561.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/imdb_2_en_5.5.0_3.0_1725775349561.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("imdb_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("imdb_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|imdb_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/draghicivlad/imdb_2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-imdb_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-imdb_2_pipeline_en.md
new file mode 100644
index 00000000000000..19c4d6900e0544
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-imdb_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English imdb_2_pipeline pipeline DistilBertForSequenceClassification from draghicivlad
+author: John Snow Labs
+name: imdb_2_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`imdb_2_pipeline` is a English model originally trained by draghicivlad.
+
+{:.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/imdb_2_pipeline_en_5.5.0_3.0_1725775361849.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/imdb_2_pipeline_en_5.5.0_3.0_1725775361849.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
+
+pipeline = PretrainedPipeline("imdb_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("imdb_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|imdb_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/draghicivlad/imdb_2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-intent_distilbert_classifier_en.md b/docs/_posts/ahmedlone127/2024-09-08-intent_distilbert_classifier_en.md
new file mode 100644
index 00000000000000..c8a3e4dd9736ab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-intent_distilbert_classifier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English intent_distilbert_classifier DistilBertForSequenceClassification from Maaz911
+author: John Snow Labs
+name: intent_distilbert_classifier
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`intent_distilbert_classifier` is a English model originally trained by Maaz911.
+
+{:.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/intent_distilbert_classifier_en_5.5.0_3.0_1725764540731.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/intent_distilbert_classifier_en_5.5.0_3.0_1725764540731.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("intent_distilbert_classifier","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("intent_distilbert_classifier", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|intent_distilbert_classifier|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Maaz911/intent-distilbert-classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-jigsaw_toxic_comments_en.md b/docs/_posts/ahmedlone127/2024-09-08-jigsaw_toxic_comments_en.md
new file mode 100644
index 00000000000000..66436b10cc95ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-jigsaw_toxic_comments_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English jigsaw_toxic_comments DistilBertForSequenceClassification from cursoai
+author: John Snow Labs
+name: jigsaw_toxic_comments
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`jigsaw_toxic_comments` is a English model originally trained by cursoai.
+
+{:.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/jigsaw_toxic_comments_en_5.5.0_3.0_1725777070323.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/jigsaw_toxic_comments_en_5.5.0_3.0_1725777070323.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("jigsaw_toxic_comments","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("jigsaw_toxic_comments", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|jigsaw_toxic_comments|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/cursoai/jigsaw-toxic-comments
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-joo_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-joo_pipeline_en.md
new file mode 100644
index 00000000000000..f9b024058ed11d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-joo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English joo_pipeline pipeline DistilBertForSequenceClassification from joohwan
+author: John Snow Labs
+name: joo_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`joo_pipeline` is a English model originally trained by joohwan.
+
+{:.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/joo_pipeline_en_5.5.0_3.0_1725776801261.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/joo_pipeline_en_5.5.0_3.0_1725776801261.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
+
+pipeline = PretrainedPipeline("joo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("joo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|joo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/joohwan/joo
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-lab1_finetuning_haochenhe_en.md b/docs/_posts/ahmedlone127/2024-09-08-lab1_finetuning_haochenhe_en.md
new file mode 100644
index 00000000000000..a06a85b6339c51
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-lab1_finetuning_haochenhe_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English lab1_finetuning_haochenhe MarianTransformer from haochenhe
+author: John Snow Labs
+name: lab1_finetuning_haochenhe
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lab1_finetuning_haochenhe` is a English model originally trained by haochenhe.
+
+{:.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/lab1_finetuning_haochenhe_en_5.5.0_3.0_1725839940943.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lab1_finetuning_haochenhe_en_5.5.0_3.0_1725839940943.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("lab1_finetuning_haochenhe","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("lab1_finetuning_haochenhe","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lab1_finetuning_haochenhe|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.1 MB|
+
+## References
+
+https://huggingface.co/haochenhe/lab1_finetuning
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-lab1_finetuning_haochenhe_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-lab1_finetuning_haochenhe_pipeline_en.md
new file mode 100644
index 00000000000000..28106fb694d33f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-lab1_finetuning_haochenhe_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English lab1_finetuning_haochenhe_pipeline pipeline MarianTransformer from haochenhe
+author: John Snow Labs
+name: lab1_finetuning_haochenhe_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lab1_finetuning_haochenhe_pipeline` is a English model originally trained by haochenhe.
+
+{:.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/lab1_finetuning_haochenhe_pipeline_en_5.5.0_3.0_1725839966974.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lab1_finetuning_haochenhe_pipeline_en_5.5.0_3.0_1725839966974.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
+
+pipeline = PretrainedPipeline("lab1_finetuning_haochenhe_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lab1_finetuning_haochenhe_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lab1_finetuning_haochenhe_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|508.6 MB|
+
+## References
+
+https://huggingface.co/haochenhe/lab1_finetuning
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-lab1_finetuning_lailemon_en.md b/docs/_posts/ahmedlone127/2024-09-08-lab1_finetuning_lailemon_en.md
new file mode 100644
index 00000000000000..1f942d3805e429
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-lab1_finetuning_lailemon_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English lab1_finetuning_lailemon MarianTransformer from LaiLemon
+author: John Snow Labs
+name: lab1_finetuning_lailemon
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lab1_finetuning_lailemon` is a English model originally trained by LaiLemon.
+
+{:.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/lab1_finetuning_lailemon_en_5.5.0_3.0_1725831334565.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lab1_finetuning_lailemon_en_5.5.0_3.0_1725831334565.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("lab1_finetuning_lailemon","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("lab1_finetuning_lailemon","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lab1_finetuning_lailemon|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.3 MB|
+
+## References
+
+https://huggingface.co/LaiLemon/lab1_finetuning
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-lab1_random_lailemon_en.md b/docs/_posts/ahmedlone127/2024-09-08-lab1_random_lailemon_en.md
new file mode 100644
index 00000000000000..118a2ecf407111
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-lab1_random_lailemon_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English lab1_random_lailemon MarianTransformer from LaiLemon
+author: John Snow Labs
+name: lab1_random_lailemon
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lab1_random_lailemon` is a English model originally trained by LaiLemon.
+
+{:.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/lab1_random_lailemon_en_5.5.0_3.0_1725832197663.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lab1_random_lailemon_en_5.5.0_3.0_1725832197663.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("lab1_random_lailemon","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("lab1_random_lailemon","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lab1_random_lailemon|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|509.8 MB|
+
+## References
+
+https://huggingface.co/LaiLemon/lab1_random
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-lab2_efficient_reshphil_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-lab2_efficient_reshphil_pipeline_en.md
new file mode 100644
index 00000000000000..2a526221c33edb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-lab2_efficient_reshphil_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English lab2_efficient_reshphil_pipeline pipeline MarianTransformer from Reshphil
+author: John Snow Labs
+name: lab2_efficient_reshphil_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lab2_efficient_reshphil_pipeline` is a English model originally trained by Reshphil.
+
+{:.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/lab2_efficient_reshphil_pipeline_en_5.5.0_3.0_1725766547097.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lab2_efficient_reshphil_pipeline_en_5.5.0_3.0_1725766547097.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
+
+pipeline = PretrainedPipeline("lab2_efficient_reshphil_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lab2_efficient_reshphil_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lab2_efficient_reshphil_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|508.9 MB|
+
+## References
+
+https://huggingface.co/Reshphil/lab2_efficient
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-language_detection_en.md b/docs/_posts/ahmedlone127/2024-09-08-language_detection_en.md
new file mode 100644
index 00000000000000..ba748156efb608
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-language_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English language_detection XlmRoBertaForSequenceClassification from eleldar
+author: John Snow Labs
+name: language_detection
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`language_detection` is a English model originally trained by eleldar.
+
+{:.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/language_detection_en_5.5.0_3.0_1725799666847.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/language_detection_en_5.5.0_3.0_1725799666847.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("language_detection","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("language_detection", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|language_detection|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|870.4 MB|
+
+## References
+
+https://huggingface.co/eleldar/language-detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-language_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-language_detection_pipeline_en.md
new file mode 100644
index 00000000000000..9f5c14e9c50a4e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-language_detection_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English language_detection_pipeline pipeline XlmRoBertaForSequenceClassification from eleldar
+author: John Snow Labs
+name: language_detection_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`language_detection_pipeline` is a English model originally trained by eleldar.
+
+{:.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/language_detection_pipeline_en_5.5.0_3.0_1725799771234.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/language_detection_pipeline_en_5.5.0_3.0_1725799771234.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
+
+pipeline = PretrainedPipeline("language_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("language_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|language_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|870.4 MB|
+
+## References
+
+https://huggingface.co/eleldar/language-detection
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-legal_roberta_large_en.md b/docs/_posts/ahmedlone127/2024-09-08-legal_roberta_large_en.md
new file mode 100644
index 00000000000000..eea63a06928e46
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-legal_roberta_large_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English legal_roberta_large RoBertaForSequenceClassification from frisibeli
+author: John Snow Labs
+name: legal_roberta_large
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legal_roberta_large` is a English model originally trained by frisibeli.
+
+{:.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/legal_roberta_large_en_5.5.0_3.0_1725830736555.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_roberta_large_en_5.5.0_3.0_1725830736555.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("legal_roberta_large","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("legal_roberta_large", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|legal_roberta_large|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/frisibeli/legal-roberta-large
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-legal_roberta_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-legal_roberta_large_pipeline_en.md
new file mode 100644
index 00000000000000..d5e59342ce3a58
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-legal_roberta_large_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English legal_roberta_large_pipeline pipeline RoBertaForSequenceClassification from frisibeli
+author: John Snow Labs
+name: legal_roberta_large_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legal_roberta_large_pipeline` is a English model originally trained by frisibeli.
+
+{:.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/legal_roberta_large_pipeline_en_5.5.0_3.0_1725830806268.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_roberta_large_pipeline_en_5.5.0_3.0_1725830806268.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
+
+pipeline = PretrainedPipeline("legal_roberta_large_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("legal_roberta_large_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|legal_roberta_large_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/frisibeli/legal-roberta-large
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-lenu_at_en.md b/docs/_posts/ahmedlone127/2024-09-08-lenu_at_en.md
new file mode 100644
index 00000000000000..7e8be6919e2f47
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-lenu_at_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English lenu_at BertForSequenceClassification from Sociovestix
+author: John Snow Labs
+name: lenu_at
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lenu_at` is a English model originally trained by Sociovestix.
+
+{:.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/lenu_at_en_5.5.0_3.0_1725802198117.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lenu_at_en_5.5.0_3.0_1725802198117.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("lenu_at","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("lenu_at", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lenu_at|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|412.2 MB|
+
+## References
+
+https://huggingface.co/Sociovestix/lenu_AT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-lenu_at_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-lenu_at_pipeline_en.md
new file mode 100644
index 00000000000000..fef4ee0ead20dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-lenu_at_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English lenu_at_pipeline pipeline BertForSequenceClassification from Sociovestix
+author: John Snow Labs
+name: lenu_at_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lenu_at_pipeline` is a English model originally trained by Sociovestix.
+
+{:.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/lenu_at_pipeline_en_5.5.0_3.0_1725802217578.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lenu_at_pipeline_en_5.5.0_3.0_1725802217578.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
+
+pipeline = PretrainedPipeline("lenu_at_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lenu_at_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lenu_at_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|412.2 MB|
+
+## References
+
+https://huggingface.co/Sociovestix/lenu_AT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-lenu_chamorro_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-lenu_chamorro_pipeline_en.md
new file mode 100644
index 00000000000000..52742730689e17
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-lenu_chamorro_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English lenu_chamorro_pipeline pipeline BertForSequenceClassification from Sociovestix
+author: John Snow Labs
+name: lenu_chamorro_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lenu_chamorro_pipeline` is a English model originally trained by Sociovestix.
+
+{:.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/lenu_chamorro_pipeline_en_5.5.0_3.0_1725761686888.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lenu_chamorro_pipeline_en_5.5.0_3.0_1725761686888.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
+
+pipeline = PretrainedPipeline("lenu_chamorro_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lenu_chamorro_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lenu_chamorro_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|627.8 MB|
+
+## References
+
+https://huggingface.co/Sociovestix/lenu_CH
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-lenu_dk_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-lenu_dk_pipeline_en.md
new file mode 100644
index 00000000000000..274a7aa08e957a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-lenu_dk_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English lenu_dk_pipeline pipeline BertForSequenceClassification from Sociovestix
+author: John Snow Labs
+name: lenu_dk_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lenu_dk_pipeline` is a English model originally trained by Sociovestix.
+
+{:.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/lenu_dk_pipeline_en_5.5.0_3.0_1725802095056.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lenu_dk_pipeline_en_5.5.0_3.0_1725802095056.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
+
+pipeline = PretrainedPipeline("lenu_dk_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lenu_dk_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lenu_dk_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|414.6 MB|
+
+## References
+
+https://huggingface.co/Sociovestix/lenu_DK
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-lenu_hungarian_en.md b/docs/_posts/ahmedlone127/2024-09-08-lenu_hungarian_en.md
new file mode 100644
index 00000000000000..a91f6acd44a970
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-lenu_hungarian_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English lenu_hungarian BertForSequenceClassification from Sociovestix
+author: John Snow Labs
+name: lenu_hungarian
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lenu_hungarian` is a English model originally trained by Sociovestix.
+
+{:.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/lenu_hungarian_en_5.5.0_3.0_1725801616524.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lenu_hungarian_en_5.5.0_3.0_1725801616524.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("lenu_hungarian","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("lenu_hungarian", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lenu_hungarian|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|627.8 MB|
+
+## References
+
+https://huggingface.co/Sociovestix/lenu_HU
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-lenu_hungarian_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-lenu_hungarian_pipeline_en.md
new file mode 100644
index 00000000000000..2e70f115aafee7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-lenu_hungarian_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English lenu_hungarian_pipeline pipeline BertForSequenceClassification from Sociovestix
+author: John Snow Labs
+name: lenu_hungarian_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lenu_hungarian_pipeline` is a English model originally trained by Sociovestix.
+
+{:.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/lenu_hungarian_pipeline_en_5.5.0_3.0_1725801647795.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lenu_hungarian_pipeline_en_5.5.0_3.0_1725801647795.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
+
+pipeline = PretrainedPipeline("lenu_hungarian_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lenu_hungarian_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lenu_hungarian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|627.9 MB|
+
+## References
+
+https://huggingface.co/Sociovestix/lenu_HU
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-lenu_limburgish_en.md b/docs/_posts/ahmedlone127/2024-09-08-lenu_limburgish_en.md
new file mode 100644
index 00000000000000..aecc609917095f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-lenu_limburgish_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English lenu_limburgish BertForSequenceClassification from Sociovestix
+author: John Snow Labs
+name: lenu_limburgish
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lenu_limburgish` is a English model originally trained by Sociovestix.
+
+{:.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/lenu_limburgish_en_5.5.0_3.0_1725819841684.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lenu_limburgish_en_5.5.0_3.0_1725819841684.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("lenu_limburgish","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("lenu_limburgish", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lenu_limburgish|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|627.8 MB|
+
+## References
+
+https://huggingface.co/Sociovestix/lenu_LI
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-lenu_polish_en.md b/docs/_posts/ahmedlone127/2024-09-08-lenu_polish_en.md
new file mode 100644
index 00000000000000..e5e25a71a9a51f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-lenu_polish_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English lenu_polish BertForSequenceClassification from Sociovestix
+author: John Snow Labs
+name: lenu_polish
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lenu_polish` is a English model originally trained by Sociovestix.
+
+{:.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/lenu_polish_en_5.5.0_3.0_1725761108221.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lenu_polish_en_5.5.0_3.0_1725761108221.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("lenu_polish","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("lenu_polish", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lenu_polish|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|495.9 MB|
+
+## References
+
+https://huggingface.co/Sociovestix/lenu_PL
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-lenu_us_catalan_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-lenu_us_catalan_pipeline_en.md
new file mode 100644
index 00000000000000..c73fd363dc5a02
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-lenu_us_catalan_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English lenu_us_catalan_pipeline pipeline BertForSequenceClassification from Sociovestix
+author: John Snow Labs
+name: lenu_us_catalan_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lenu_us_catalan_pipeline` is a English model originally trained by Sociovestix.
+
+{:.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/lenu_us_catalan_pipeline_en_5.5.0_3.0_1725768583125.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lenu_us_catalan_pipeline_en_5.5.0_3.0_1725768583125.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
+
+pipeline = PretrainedPipeline("lenu_us_catalan_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lenu_us_catalan_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lenu_us_catalan_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.5 MB|
+
+## References
+
+https://huggingface.co/Sociovestix/lenu_US-CA
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-linkbert_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-linkbert_base_pipeline_en.md
new file mode 100644
index 00000000000000..72f27b58c04a36
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-linkbert_base_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English linkbert_base_pipeline pipeline BertForSequenceClassification from michiyasunaga
+author: John Snow Labs
+name: linkbert_base_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`linkbert_base_pipeline` is a English model originally trained by michiyasunaga.
+
+{:.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/linkbert_base_pipeline_en_5.5.0_3.0_1725768315158.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/linkbert_base_pipeline_en_5.5.0_3.0_1725768315158.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
+
+pipeline = PretrainedPipeline("linkbert_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("linkbert_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|linkbert_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|405.6 MB|
+
+## References
+
+https://huggingface.co/michiyasunaga/LinkBERT-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-local_politics_en.md b/docs/_posts/ahmedlone127/2024-09-08-local_politics_en.md
new file mode 100644
index 00000000000000..88eef918872a4e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-local_politics_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English local_politics BertForSequenceClassification from nruigrok
+author: John Snow Labs
+name: local_politics
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`local_politics` is a English model originally trained by nruigrok.
+
+{:.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/local_politics_en_5.5.0_3.0_1725761744894.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/local_politics_en_5.5.0_3.0_1725761744894.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("local_politics","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("local_politics", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|local_politics|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.0 MB|
+
+## References
+
+https://huggingface.co/nruigrok/local_politics
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-longformer_squad_becas_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-longformer_squad_becas_1_pipeline_en.md
new file mode 100644
index 00000000000000..95feebf9324178
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-longformer_squad_becas_1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English longformer_squad_becas_1_pipeline pipeline RoBertaForQuestionAnswering from BecarIA
+author: John Snow Labs
+name: longformer_squad_becas_1_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`longformer_squad_becas_1_pipeline` is a English model originally trained by BecarIA.
+
+{:.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/longformer_squad_becas_1_pipeline_en_5.5.0_3.0_1725834164364.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/longformer_squad_becas_1_pipeline_en_5.5.0_3.0_1725834164364.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
+
+pipeline = PretrainedPipeline("longformer_squad_becas_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("longformer_squad_becas_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|longformer_squad_becas_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|473.3 MB|
+
+## References
+
+https://huggingface.co/BecarIA/Longformer-SQuAD-becas-1
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-lthien_tra_bai_corsican_phuong_pipeline_nan.md b/docs/_posts/ahmedlone127/2024-09-08-lthien_tra_bai_corsican_phuong_pipeline_nan.md
new file mode 100644
index 00000000000000..ec97cd4012b526
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-lthien_tra_bai_corsican_phuong_pipeline_nan.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: None lthien_tra_bai_corsican_phuong_pipeline pipeline DistilBertForQuestionAnswering from hi113
+author: John Snow Labs
+name: lthien_tra_bai_corsican_phuong_pipeline
+date: 2024-09-08
+tags: [nan, open_source, pipeline, onnx]
+task: Question Answering
+language: nan
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lthien_tra_bai_corsican_phuong_pipeline` is a None model originally trained by hi113.
+
+{:.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/lthien_tra_bai_corsican_phuong_pipeline_nan_5.5.0_3.0_1725818455337.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lthien_tra_bai_corsican_phuong_pipeline_nan_5.5.0_3.0_1725818455337.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
+
+pipeline = PretrainedPipeline("lthien_tra_bai_corsican_phuong_pipeline", lang = "nan")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lthien_tra_bai_corsican_phuong_pipeline", lang = "nan")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lthien_tra_bai_corsican_phuong_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|nan|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/hi113/ltHien_Tra_Bai_Co_Phuong
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-luganda_ner_v1_en.md b/docs/_posts/ahmedlone127/2024-09-08-luganda_ner_v1_en.md
new file mode 100644
index 00000000000000..fbb3d757ec88ab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-luganda_ner_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English luganda_ner_v1 XlmRoBertaForTokenClassification from Conrad747
+author: John Snow Labs
+name: luganda_ner_v1
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`luganda_ner_v1` is a English model originally trained by Conrad747.
+
+{:.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/luganda_ner_v1_en_5.5.0_3.0_1725772720378.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/luganda_ner_v1_en_5.5.0_3.0_1725772720378.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("luganda_ner_v1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("luganda_ner_v1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|luganda_ner_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|835.6 MB|
+
+## References
+
+https://huggingface.co/Conrad747/luganda-ner-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-maltese_coref_english_arabic_gender_en.md b/docs/_posts/ahmedlone127/2024-09-08-maltese_coref_english_arabic_gender_en.md
new file mode 100644
index 00000000000000..0568ed8d9456fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-maltese_coref_english_arabic_gender_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English maltese_coref_english_arabic_gender MarianTransformer from nlphuji
+author: John Snow Labs
+name: maltese_coref_english_arabic_gender
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`maltese_coref_english_arabic_gender` is a English model originally trained by nlphuji.
+
+{:.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/maltese_coref_english_arabic_gender_en_5.5.0_3.0_1725795377081.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/maltese_coref_english_arabic_gender_en_5.5.0_3.0_1725795377081.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("maltese_coref_english_arabic_gender","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("maltese_coref_english_arabic_gender","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|maltese_coref_english_arabic_gender|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|528.7 MB|
+
+## References
+
+https://huggingface.co/nlphuji/mt_coref_en_ar_gender
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-maltese_hitz_basque_spanish_eu.md b/docs/_posts/ahmedlone127/2024-09-08-maltese_hitz_basque_spanish_eu.md
new file mode 100644
index 00000000000000..ebf5871fab95fd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-maltese_hitz_basque_spanish_eu.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Basque maltese_hitz_basque_spanish MarianTransformer from HiTZ
+author: John Snow Labs
+name: maltese_hitz_basque_spanish
+date: 2024-09-08
+tags: [eu, open_source, onnx, translation, marian]
+task: Translation
+language: eu
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`maltese_hitz_basque_spanish` is a Basque model originally trained by HiTZ.
+
+{:.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/maltese_hitz_basque_spanish_eu_5.5.0_3.0_1725831839966.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/maltese_hitz_basque_spanish_eu_5.5.0_3.0_1725831839966.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("maltese_hitz_basque_spanish","eu") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("maltese_hitz_basque_spanish","eu") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|maltese_hitz_basque_spanish|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|eu|
+|Size:|225.4 MB|
+
+## References
+
+https://huggingface.co/HiTZ/mt-hitz-eu-es
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-malurl_roberta_5000_95_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-malurl_roberta_5000_95_pipeline_en.md
new file mode 100644
index 00000000000000..7f64a8717236aa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-malurl_roberta_5000_95_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English malurl_roberta_5000_95_pipeline pipeline RoBertaForSequenceClassification from bgspaditya
+author: John Snow Labs
+name: malurl_roberta_5000_95_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`malurl_roberta_5000_95_pipeline` is a English model originally trained by bgspaditya.
+
+{:.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/malurl_roberta_5000_95_pipeline_en_5.5.0_3.0_1725830546839.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/malurl_roberta_5000_95_pipeline_en_5.5.0_3.0_1725830546839.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
+
+pipeline = PretrainedPipeline("malurl_roberta_5000_95_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("malurl_roberta_5000_95_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|malurl_roberta_5000_95_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|438.4 MB|
+
+## References
+
+https://huggingface.co/bgspaditya/malurl-roberta-5000-95
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-marabert22_model_en.md b/docs/_posts/ahmedlone127/2024-09-08-marabert22_model_en.md
new file mode 100644
index 00000000000000..37bc3fa3a6644d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-marabert22_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English marabert22_model BertForSequenceClassification from aya2003
+author: John Snow Labs
+name: marabert22_model
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marabert22_model` is a English model originally trained by aya2003.
+
+{:.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/marabert22_model_en_5.5.0_3.0_1725826032628.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marabert22_model_en_5.5.0_3.0_1725826032628.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("marabert22_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("marabert22_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marabert22_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|610.9 MB|
+
+## References
+
+https://huggingface.co/aya2003/marabert22-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_combined_dataset_substituted_1_1_en.md b/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_combined_dataset_substituted_1_1_en.md
new file mode 100644
index 00000000000000..eac257e248a6fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_combined_dataset_substituted_1_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English marian_finetuned_combined_dataset_substituted_1_1 MarianTransformer from kalcho100
+author: John Snow Labs
+name: marian_finetuned_combined_dataset_substituted_1_1
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_combined_dataset_substituted_1_1` is a English model originally trained by kalcho100.
+
+{:.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/marian_finetuned_combined_dataset_substituted_1_1_en_5.5.0_3.0_1725832393883.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_combined_dataset_substituted_1_1_en_5.5.0_3.0_1725832393883.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("marian_finetuned_combined_dataset_substituted_1_1","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("marian_finetuned_combined_dataset_substituted_1_1","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_combined_dataset_substituted_1_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|547.8 MB|
+
+## References
+
+https://huggingface.co/kalcho100/Marian-finetuned_combined_dataset_substituted_1_1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kde4_english_tonga_tonga_islands_chinese_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kde4_english_tonga_tonga_islands_chinese_pipeline_en.md
new file mode 100644
index 00000000000000..9617afa61fbc44
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kde4_english_tonga_tonga_islands_chinese_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_chinese_pipeline pipeline MarianTransformer from C-pangpang
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_chinese_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_chinese_pipeline` is a English model originally trained by C-pangpang.
+
+{:.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/marian_finetuned_kde4_english_tonga_tonga_islands_chinese_pipeline_en_5.5.0_3.0_1725831328932.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_chinese_pipeline_en_5.5.0_3.0_1725831328932.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
+
+pipeline = PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_chinese_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_chinese_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_chinese_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|541.1 MB|
+
+## References
+
+https://huggingface.co/C-pangpang/marian-finetuned-kde4-en-to-zh
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kde4_english_tonga_tonga_islands_french_arham061_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kde4_english_tonga_tonga_islands_french_arham061_pipeline_en.md
new file mode 100644
index 00000000000000..353b137486ff34
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kde4_english_tonga_tonga_islands_french_arham061_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_arham061_pipeline pipeline MarianTransformer from arham061
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_arham061_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_arham061_pipeline` is a English model originally trained by arham061.
+
+{:.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/marian_finetuned_kde4_english_tonga_tonga_islands_french_arham061_pipeline_en_5.5.0_3.0_1725795751440.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_arham061_pipeline_en_5.5.0_3.0_1725795751440.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
+
+pipeline = PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_arham061_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_arham061_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_arham061_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|508.7 MB|
+
+## References
+
+https://huggingface.co/arham061/marian-finetuned-kde4-en-to-fr
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kde4_english_tonga_tonga_islands_french_chloe018_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kde4_english_tonga_tonga_islands_french_chloe018_pipeline_en.md
new file mode 100644
index 00000000000000..ff23732912f8ec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kde4_english_tonga_tonga_islands_french_chloe018_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_chloe018_pipeline pipeline MarianTransformer from chloe018
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_chloe018_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_chloe018_pipeline` is a English model originally trained by chloe018.
+
+{:.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/marian_finetuned_kde4_english_tonga_tonga_islands_french_chloe018_pipeline_en_5.5.0_3.0_1725824148826.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_chloe018_pipeline_en_5.5.0_3.0_1725824148826.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
+
+pipeline = PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_chloe018_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_chloe018_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_chloe018_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|508.8 MB|
+
+## References
+
+https://huggingface.co/chloe018/marian-finetuned-kde4-en-to-fr
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kde4_english_tonga_tonga_islands_french_farfalla_en.md b/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kde4_english_tonga_tonga_islands_french_farfalla_en.md
new file mode 100644
index 00000000000000..d8da38bf33f411
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kde4_english_tonga_tonga_islands_french_farfalla_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_farfalla MarianTransformer from farfalla
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_farfalla
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_farfalla` is a English model originally trained by farfalla.
+
+{:.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/marian_finetuned_kde4_english_tonga_tonga_islands_french_farfalla_en_5.5.0_3.0_1725831640582.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_farfalla_en_5.5.0_3.0_1725831640582.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_farfalla","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_farfalla","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_farfalla|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.1 MB|
+
+## References
+
+https://huggingface.co/farfalla/marian-finetuned-kde4-en-to-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kde4_english_tonga_tonga_islands_french_huang134_en.md b/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kde4_english_tonga_tonga_islands_french_huang134_en.md
new file mode 100644
index 00000000000000..d3dae4bfa7e825
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kde4_english_tonga_tonga_islands_french_huang134_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_huang134 MarianTransformer from huang134
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_huang134
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_huang134` is a English model originally trained by huang134.
+
+{:.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/marian_finetuned_kde4_english_tonga_tonga_islands_french_huang134_en_5.5.0_3.0_1725831291126.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_huang134_en_5.5.0_3.0_1725831291126.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_huang134","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_huang134","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_huang134|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.1 MB|
+
+## References
+
+https://huggingface.co/huang134/marian-finetuned-kde4-en-to-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kde4_english_tonga_tonga_islands_french_huang134_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kde4_english_tonga_tonga_islands_french_huang134_pipeline_en.md
new file mode 100644
index 00000000000000..57e220aea72de4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kde4_english_tonga_tonga_islands_french_huang134_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_huang134_pipeline pipeline MarianTransformer from huang134
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_huang134_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_huang134_pipeline` is a English model originally trained by huang134.
+
+{:.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/marian_finetuned_kde4_english_tonga_tonga_islands_french_huang134_pipeline_en_5.5.0_3.0_1725831326344.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_huang134_pipeline_en_5.5.0_3.0_1725831326344.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
+
+pipeline = PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_huang134_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_huang134_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_huang134_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|508.7 MB|
+
+## References
+
+https://huggingface.co/huang134/marian-finetuned-kde4-en-to-fr
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kde4_english_tonga_tonga_islands_french_jaese_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kde4_english_tonga_tonga_islands_french_jaese_pipeline_en.md
new file mode 100644
index 00000000000000..b3dc804629e654
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kde4_english_tonga_tonga_islands_french_jaese_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_jaese_pipeline pipeline MarianTransformer from jaese
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_jaese_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_jaese_pipeline` is a English model originally trained by jaese.
+
+{:.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/marian_finetuned_kde4_english_tonga_tonga_islands_french_jaese_pipeline_en_5.5.0_3.0_1725832252896.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_jaese_pipeline_en_5.5.0_3.0_1725832252896.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
+
+pipeline = PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_jaese_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_jaese_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_jaese_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|508.8 MB|
+
+## References
+
+https://huggingface.co/jaese/marian-finetuned-kde4-en-to-fr
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kde4_english_tonga_tonga_islands_french_nielso_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kde4_english_tonga_tonga_islands_french_nielso_pipeline_en.md
new file mode 100644
index 00000000000000..a8b3298911a9f2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kde4_english_tonga_tonga_islands_french_nielso_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_nielso_pipeline pipeline MarianTransformer from nielso
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_nielso_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_nielso_pipeline` is a English model originally trained by nielso.
+
+{:.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/marian_finetuned_kde4_english_tonga_tonga_islands_french_nielso_pipeline_en_5.5.0_3.0_1725831327899.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_nielso_pipeline_en_5.5.0_3.0_1725831327899.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
+
+pipeline = PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_nielso_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_nielso_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_nielso_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|508.7 MB|
+
+## References
+
+https://huggingface.co/nielso/marian-finetuned-kde4-en-to-fr
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kde4_english_tonga_tonga_islands_french_uiji_en.md b/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kde4_english_tonga_tonga_islands_french_uiji_en.md
new file mode 100644
index 00000000000000..4365e006169079
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kde4_english_tonga_tonga_islands_french_uiji_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_uiji MarianTransformer from Uiji
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_uiji
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_uiji` is a English model originally trained by Uiji.
+
+{:.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/marian_finetuned_kde4_english_tonga_tonga_islands_french_uiji_en_5.5.0_3.0_1725796219780.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_uiji_en_5.5.0_3.0_1725796219780.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_uiji","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_uiji","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_uiji|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.1 MB|
+
+## References
+
+https://huggingface.co/Uiji/marian-finetuned-kde4-en-to-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kftt_japanese_tonga_tonga_islands_english_test3_en.md b/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kftt_japanese_tonga_tonga_islands_english_test3_en.md
new file mode 100644
index 00000000000000..0217dbb35cc1c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kftt_japanese_tonga_tonga_islands_english_test3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English marian_finetuned_kftt_japanese_tonga_tonga_islands_english_test3 MarianTransformer from sephinroth
+author: John Snow Labs
+name: marian_finetuned_kftt_japanese_tonga_tonga_islands_english_test3
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kftt_japanese_tonga_tonga_islands_english_test3` is a English model originally trained by sephinroth.
+
+{:.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/marian_finetuned_kftt_japanese_tonga_tonga_islands_english_test3_en_5.5.0_3.0_1725795833645.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kftt_japanese_tonga_tonga_islands_english_test3_en_5.5.0_3.0_1725795833645.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("marian_finetuned_kftt_japanese_tonga_tonga_islands_english_test3","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("marian_finetuned_kftt_japanese_tonga_tonga_islands_english_test3","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kftt_japanese_tonga_tonga_islands_english_test3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|515.2 MB|
+
+## References
+
+https://huggingface.co/sephinroth/marian-finetuned-kftt-ja-to-en-test3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kftt_japanese_tonga_tonga_islands_english_test3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_kftt_japanese_tonga_tonga_islands_english_test3_pipeline_en.md
new file mode 100644
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--- /dev/null
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@@ -0,0 +1,70 @@
+---
+layout: model
+title: English marian_finetuned_kftt_japanese_tonga_tonga_islands_english_test3_pipeline pipeline MarianTransformer from sephinroth
+author: John Snow Labs
+name: marian_finetuned_kftt_japanese_tonga_tonga_islands_english_test3_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kftt_japanese_tonga_tonga_islands_english_test3_pipeline` is a English model originally trained by sephinroth.
+
+{:.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/marian_finetuned_kftt_japanese_tonga_tonga_islands_english_test3_pipeline_en_5.5.0_3.0_1725795858333.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kftt_japanese_tonga_tonga_islands_english_test3_pipeline_en_5.5.0_3.0_1725795858333.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
+
+pipeline = PretrainedPipeline("marian_finetuned_kftt_japanese_tonga_tonga_islands_english_test3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("marian_finetuned_kftt_japanese_tonga_tonga_islands_english_test3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kftt_japanese_tonga_tonga_islands_english_test3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|515.8 MB|
+
+## References
+
+https://huggingface.co/sephinroth/marian-finetuned-kftt-ja-to-en-test3
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_opus100_english_tonga_tonga_islands_russian_accelerate_en.md b/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_opus100_english_tonga_tonga_islands_russian_accelerate_en.md
new file mode 100644
index 00000000000000..98505bd3070aa8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_opus100_english_tonga_tonga_islands_russian_accelerate_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English marian_finetuned_opus100_english_tonga_tonga_islands_russian_accelerate MarianTransformer from rinkorn
+author: John Snow Labs
+name: marian_finetuned_opus100_english_tonga_tonga_islands_russian_accelerate
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_opus100_english_tonga_tonga_islands_russian_accelerate` is a English model originally trained by rinkorn.
+
+{:.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/marian_finetuned_opus100_english_tonga_tonga_islands_russian_accelerate_en_5.5.0_3.0_1725795349849.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_opus100_english_tonga_tonga_islands_russian_accelerate_en_5.5.0_3.0_1725795349849.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("marian_finetuned_opus100_english_tonga_tonga_islands_russian_accelerate","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("marian_finetuned_opus100_english_tonga_tonga_islands_russian_accelerate","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_opus100_english_tonga_tonga_islands_russian_accelerate|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|525.5 MB|
+
+## References
+
+https://huggingface.co/rinkorn/marian-finetuned-opus100-en-to-ru-accelerate
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_opus100_english_tonga_tonga_islands_russian_accelerate_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-marian_finetuned_opus100_english_tonga_tonga_islands_russian_accelerate_pipeline_en.md
new file mode 100644
index 00000000000000..4e3377ad942fb6
--- /dev/null
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@@ -0,0 +1,70 @@
+---
+layout: model
+title: English marian_finetuned_opus100_english_tonga_tonga_islands_russian_accelerate_pipeline pipeline MarianTransformer from rinkorn
+author: John Snow Labs
+name: marian_finetuned_opus100_english_tonga_tonga_islands_russian_accelerate_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_opus100_english_tonga_tonga_islands_russian_accelerate_pipeline` is a English model originally trained by rinkorn.
+
+{:.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/marian_finetuned_opus100_english_tonga_tonga_islands_russian_accelerate_pipeline_en_5.5.0_3.0_1725795375127.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_opus100_english_tonga_tonga_islands_russian_accelerate_pipeline_en_5.5.0_3.0_1725795375127.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
+
+pipeline = PretrainedPipeline("marian_finetuned_opus100_english_tonga_tonga_islands_russian_accelerate_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("marian_finetuned_opus100_english_tonga_tonga_islands_russian_accelerate_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_opus100_english_tonga_tonga_islands_russian_accelerate_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|526.0 MB|
+
+## References
+
+https://huggingface.co/rinkorn/marian-finetuned-opus100-en-to-ru-accelerate
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-marian_random_kde4_english_tonga_tonga_islands_french_chloehuang1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-marian_random_kde4_english_tonga_tonga_islands_french_chloehuang1_pipeline_en.md
new file mode 100644
index 00000000000000..6f2292a9c586e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-marian_random_kde4_english_tonga_tonga_islands_french_chloehuang1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English marian_random_kde4_english_tonga_tonga_islands_french_chloehuang1_pipeline pipeline MarianTransformer from ChloeHuang1
+author: John Snow Labs
+name: marian_random_kde4_english_tonga_tonga_islands_french_chloehuang1_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_random_kde4_english_tonga_tonga_islands_french_chloehuang1_pipeline` is a English model originally trained by ChloeHuang1.
+
+{:.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/marian_random_kde4_english_tonga_tonga_islands_french_chloehuang1_pipeline_en_5.5.0_3.0_1725765503102.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_random_kde4_english_tonga_tonga_islands_french_chloehuang1_pipeline_en_5.5.0_3.0_1725765503102.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
+
+pipeline = PretrainedPipeline("marian_random_kde4_english_tonga_tonga_islands_french_chloehuang1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("marian_random_kde4_english_tonga_tonga_islands_french_chloehuang1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_random_kde4_english_tonga_tonga_islands_french_chloehuang1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|510.3 MB|
+
+## References
+
+https://huggingface.co/ChloeHuang1/marian-random-kde4-en-to-fr
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-mariancg_django_en.md b/docs/_posts/ahmedlone127/2024-09-08-mariancg_django_en.md
new file mode 100644
index 00000000000000..c78d436ab03c83
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-mariancg_django_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mariancg_django MarianTransformer from AhmedSSoliman
+author: John Snow Labs
+name: mariancg_django
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mariancg_django` is a English model originally trained by AhmedSSoliman.
+
+{:.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/mariancg_django_en_5.5.0_3.0_1725795999204.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mariancg_django_en_5.5.0_3.0_1725795999204.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("mariancg_django","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("mariancg_django","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mariancg_django|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|548.0 MB|
+
+## References
+
+https://huggingface.co/AhmedSSoliman/MarianCG-DJANGO
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-mariancg_django_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-mariancg_django_pipeline_en.md
new file mode 100644
index 00000000000000..c6307f9b36914e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-mariancg_django_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mariancg_django_pipeline pipeline MarianTransformer from AhmedSSoliman
+author: John Snow Labs
+name: mariancg_django_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mariancg_django_pipeline` is a English model originally trained by AhmedSSoliman.
+
+{:.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/mariancg_django_pipeline_en_5.5.0_3.0_1725796025671.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mariancg_django_pipeline_en_5.5.0_3.0_1725796025671.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
+
+pipeline = PretrainedPipeline("mariancg_django_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mariancg_django_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mariancg_django_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|548.5 MB|
+
+## References
+
+https://huggingface.co/AhmedSSoliman/MarianCG-DJANGO
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-marianmarketupdates_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-marianmarketupdates_pipeline_en.md
new file mode 100644
index 00000000000000..91b5cc98258830
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-marianmarketupdates_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English marianmarketupdates_pipeline pipeline MarianTransformer from Ahmedhisham
+author: John Snow Labs
+name: marianmarketupdates_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marianmarketupdates_pipeline` is a English model originally trained by Ahmedhisham.
+
+{:.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/marianmarketupdates_pipeline_en_5.5.0_3.0_1725766221789.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marianmarketupdates_pipeline_en_5.5.0_3.0_1725766221789.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
+
+pipeline = PretrainedPipeline("marianmarketupdates_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("marianmarketupdates_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marianmarketupdates_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|528.5 MB|
+
+## References
+
+https://huggingface.co/Ahmedhisham/marianMarketupdates
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-masked_lm_en.md b/docs/_posts/ahmedlone127/2024-09-08-masked_lm_en.md
new file mode 100644
index 00000000000000..607dd883dda976
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-masked_lm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English masked_lm DistilBertEmbeddings from ctquangdn89
+author: John Snow Labs
+name: masked_lm
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`masked_lm` is a English model originally trained by ctquangdn89.
+
+{:.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/masked_lm_en_5.5.0_3.0_1725828504040.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/masked_lm_en_5.5.0_3.0_1725828504040.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("masked_lm","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("masked_lm","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|masked_lm|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/ctquangdn89/masked-lm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-maskedlm_finetuned_imdb_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-maskedlm_finetuned_imdb_pipeline_en.md
new file mode 100644
index 00000000000000..6a9e2a41237e16
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-maskedlm_finetuned_imdb_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English maskedlm_finetuned_imdb_pipeline pipeline DistilBertEmbeddings from MRP101py
+author: John Snow Labs
+name: maskedlm_finetuned_imdb_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`maskedlm_finetuned_imdb_pipeline` is a English model originally trained by MRP101py.
+
+{:.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/maskedlm_finetuned_imdb_pipeline_en_5.5.0_3.0_1725776443487.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/maskedlm_finetuned_imdb_pipeline_en_5.5.0_3.0_1725776443487.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
+
+pipeline = PretrainedPipeline("maskedlm_finetuned_imdb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("maskedlm_finetuned_imdb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|maskedlm_finetuned_imdb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/MRP101py/MaskedLM-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-mdeberta_base_v3_7_en.md b/docs/_posts/ahmedlone127/2024-09-08-mdeberta_base_v3_7_en.md
new file mode 100644
index 00000000000000..2a927e59395b66
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-mdeberta_base_v3_7_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mdeberta_base_v3_7 DeBertaForSequenceClassification from alyazharr
+author: John Snow Labs
+name: mdeberta_base_v3_7
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_base_v3_7` is a English model originally trained by alyazharr.
+
+{:.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/mdeberta_base_v3_7_en_5.5.0_3.0_1725811123265.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_base_v3_7_en_5.5.0_3.0_1725811123265.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("mdeberta_base_v3_7","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_base_v3_7", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_base_v3_7|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|832.6 MB|
+
+## References
+
+https://huggingface.co/alyazharr/mdeberta_base_v3_7
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-mdeberta_base_v3_7_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-mdeberta_base_v3_7_pipeline_en.md
new file mode 100644
index 00000000000000..4a6b95ac85efcc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-mdeberta_base_v3_7_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mdeberta_base_v3_7_pipeline pipeline DeBertaForSequenceClassification from alyazharr
+author: John Snow Labs
+name: mdeberta_base_v3_7_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_base_v3_7_pipeline` is a English model originally trained by alyazharr.
+
+{:.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/mdeberta_base_v3_7_pipeline_en_5.5.0_3.0_1725811208563.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_base_v3_7_pipeline_en_5.5.0_3.0_1725811208563.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
+
+pipeline = PretrainedPipeline("mdeberta_base_v3_7_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_base_v3_7_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_base_v3_7_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|832.6 MB|
+
+## References
+
+https://huggingface.co/alyazharr/mdeberta_base_v3_7
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-mdeberta_v3_base_mrpc_100_en.md b/docs/_posts/ahmedlone127/2024-09-08-mdeberta_v3_base_mrpc_100_en.md
new file mode 100644
index 00000000000000..0efffc688c538c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-mdeberta_v3_base_mrpc_100_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mdeberta_v3_base_mrpc_100 DeBertaForSequenceClassification from tmnam20
+author: John Snow Labs
+name: mdeberta_v3_base_mrpc_100
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_mrpc_100` is a English model originally trained by tmnam20.
+
+{:.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/mdeberta_v3_base_mrpc_100_en_5.5.0_3.0_1725803781903.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_mrpc_100_en_5.5.0_3.0_1725803781903.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_mrpc_100","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_mrpc_100", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_mrpc_100|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|789.2 MB|
+
+## References
+
+https://huggingface.co/tmnam20/mdeberta-v3-base-mrpc-100
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-mdeberta_v3_base_mrpc_100_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-mdeberta_v3_base_mrpc_100_pipeline_en.md
new file mode 100644
index 00000000000000..7585ccc3f0c481
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-mdeberta_v3_base_mrpc_100_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mdeberta_v3_base_mrpc_100_pipeline pipeline DeBertaForSequenceClassification from tmnam20
+author: John Snow Labs
+name: mdeberta_v3_base_mrpc_100_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_mrpc_100_pipeline` is a English model originally trained by tmnam20.
+
+{:.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/mdeberta_v3_base_mrpc_100_pipeline_en_5.5.0_3.0_1725803934834.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_mrpc_100_pipeline_en_5.5.0_3.0_1725803934834.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
+
+pipeline = PretrainedPipeline("mdeberta_v3_base_mrpc_100_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_v3_base_mrpc_100_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_mrpc_100_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|789.2 MB|
+
+## References
+
+https://huggingface.co/tmnam20/mdeberta-v3-base-mrpc-100
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-med_nonmed_classifier_en.md b/docs/_posts/ahmedlone127/2024-09-08-med_nonmed_classifier_en.md
new file mode 100644
index 00000000000000..b9ee173d07dfd4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-med_nonmed_classifier_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English med_nonmed_classifier DistilBertForSequenceClassification from ai-maker-space
+author: John Snow Labs
+name: med_nonmed_classifier
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`med_nonmed_classifier` is a English model originally trained by ai-maker-space.
+
+{:.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/med_nonmed_classifier_en_5.5.0_3.0_1725776963470.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/med_nonmed_classifier_en_5.5.0_3.0_1725776963470.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("med_nonmed_classifier","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("med_nonmed_classifier", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|med_nonmed_classifier|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ai-maker-space/med_nonmed_classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-mentalroberta_4label_v2_2_en.md b/docs/_posts/ahmedlone127/2024-09-08-mentalroberta_4label_v2_2_en.md
new file mode 100644
index 00000000000000..597496f85103de
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-mentalroberta_4label_v2_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mentalroberta_4label_v2_2 RoBertaForSequenceClassification from AliaeAI
+author: John Snow Labs
+name: mentalroberta_4label_v2_2
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mentalroberta_4label_v2_2` is a English model originally trained by AliaeAI.
+
+{:.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/mentalroberta_4label_v2_2_en_5.5.0_3.0_1725821118912.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mentalroberta_4label_v2_2_en_5.5.0_3.0_1725821118912.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("mentalroberta_4label_v2_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("mentalroberta_4label_v2_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mentalroberta_4label_v2_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/AliaeAI/MentalRoBERTa_4label_v2.2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-microsoft_deberta_v3_large_cls_senteval_cree_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-microsoft_deberta_v3_large_cls_senteval_cree_pipeline_en.md
new file mode 100644
index 00000000000000..248619a3f6f426
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-microsoft_deberta_v3_large_cls_senteval_cree_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English microsoft_deberta_v3_large_cls_senteval_cree_pipeline pipeline DeBertaForSequenceClassification from ghatgetanuj
+author: John Snow Labs
+name: microsoft_deberta_v3_large_cls_senteval_cree_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`microsoft_deberta_v3_large_cls_senteval_cree_pipeline` is a English model originally trained by ghatgetanuj.
+
+{:.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/microsoft_deberta_v3_large_cls_senteval_cree_pipeline_en_5.5.0_3.0_1725812495655.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_cls_senteval_cree_pipeline_en_5.5.0_3.0_1725812495655.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
+
+pipeline = PretrainedPipeline("microsoft_deberta_v3_large_cls_senteval_cree_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("microsoft_deberta_v3_large_cls_senteval_cree_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|microsoft_deberta_v3_large_cls_senteval_cree_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/ghatgetanuj/microsoft-deberta-v3-large_cls_SentEval-CR
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-microsoft_deberta_v3_large_cls_subj_ghatgetanuj_en.md b/docs/_posts/ahmedlone127/2024-09-08-microsoft_deberta_v3_large_cls_subj_ghatgetanuj_en.md
new file mode 100644
index 00000000000000..d1ff61489384b9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-microsoft_deberta_v3_large_cls_subj_ghatgetanuj_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English microsoft_deberta_v3_large_cls_subj_ghatgetanuj DeBertaForSequenceClassification from ghatgetanuj
+author: John Snow Labs
+name: microsoft_deberta_v3_large_cls_subj_ghatgetanuj
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`microsoft_deberta_v3_large_cls_subj_ghatgetanuj` is a English model originally trained by ghatgetanuj.
+
+{:.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/microsoft_deberta_v3_large_cls_subj_ghatgetanuj_en_5.5.0_3.0_1725812205097.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/microsoft_deberta_v3_large_cls_subj_ghatgetanuj_en_5.5.0_3.0_1725812205097.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("microsoft_deberta_v3_large_cls_subj_ghatgetanuj","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("microsoft_deberta_v3_large_cls_subj_ghatgetanuj", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|microsoft_deberta_v3_large_cls_subj_ghatgetanuj|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/ghatgetanuj/microsoft-deberta-v3-large_cls_subj
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-microsoft_mpnet_mapper_aug_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-microsoft_mpnet_mapper_aug_pipeline_en.md
new file mode 100644
index 00000000000000..e11f3683c0a5e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-microsoft_mpnet_mapper_aug_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English microsoft_mpnet_mapper_aug_pipeline pipeline MPNetEmbeddings from azamat
+author: John Snow Labs
+name: microsoft_mpnet_mapper_aug_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`microsoft_mpnet_mapper_aug_pipeline` is a English model originally trained by azamat.
+
+{:.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/microsoft_mpnet_mapper_aug_pipeline_en_5.5.0_3.0_1725817558143.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/microsoft_mpnet_mapper_aug_pipeline_en_5.5.0_3.0_1725817558143.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
+
+pipeline = PretrainedPipeline("microsoft_mpnet_mapper_aug_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("microsoft_mpnet_mapper_aug_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|microsoft_mpnet_mapper_aug_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/azamat/microsoft-mpnet-mapper-aug
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-minilmv2_toxic_jigsaw_en.md b/docs/_posts/ahmedlone127/2024-09-08-minilmv2_toxic_jigsaw_en.md
new file mode 100644
index 00000000000000..29306a0584ab32
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-minilmv2_toxic_jigsaw_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English minilmv2_toxic_jigsaw BertForSequenceClassification from minuva
+author: John Snow Labs
+name: minilmv2_toxic_jigsaw
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`minilmv2_toxic_jigsaw` is a English model originally trained by minuva.
+
+{:.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/minilmv2_toxic_jigsaw_en_5.5.0_3.0_1725767838778.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/minilmv2_toxic_jigsaw_en_5.5.0_3.0_1725767838778.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("minilmv2_toxic_jigsaw","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("minilmv2_toxic_jigsaw", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|minilmv2_toxic_jigsaw|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|84.5 MB|
+
+## References
+
+https://huggingface.co/minuva/MiniLMv2-toxic-jigsaw
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-mix3_japanese_english_helsinki_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-mix3_japanese_english_helsinki_pipeline_en.md
new file mode 100644
index 00000000000000..6e2bacd17e6eb6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-mix3_japanese_english_helsinki_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mix3_japanese_english_helsinki_pipeline pipeline MarianTransformer from twieland
+author: John Snow Labs
+name: mix3_japanese_english_helsinki_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mix3_japanese_english_helsinki_pipeline` is a English model originally trained by twieland.
+
+{:.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/mix3_japanese_english_helsinki_pipeline_en_5.5.0_3.0_1725832409224.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mix3_japanese_english_helsinki_pipeline_en_5.5.0_3.0_1725832409224.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
+
+pipeline = PretrainedPipeline("mix3_japanese_english_helsinki_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mix3_japanese_english_helsinki_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mix3_japanese_english_helsinki_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|517.7 MB|
+
+## References
+
+https://huggingface.co/twieland/MIX3_ja-en_helsinki
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-mix4_japanese_english_helsinki_en.md b/docs/_posts/ahmedlone127/2024-09-08-mix4_japanese_english_helsinki_en.md
new file mode 100644
index 00000000000000..38a3f875657f0d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-mix4_japanese_english_helsinki_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mix4_japanese_english_helsinki MarianTransformer from twieland
+author: John Snow Labs
+name: mix4_japanese_english_helsinki
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mix4_japanese_english_helsinki` is a English model originally trained by twieland.
+
+{:.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/mix4_japanese_english_helsinki_en_5.5.0_3.0_1725831875168.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mix4_japanese_english_helsinki_en_5.5.0_3.0_1725831875168.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("mix4_japanese_english_helsinki","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("mix4_japanese_english_helsinki","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mix4_japanese_english_helsinki|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|516.7 MB|
+
+## References
+
+https://huggingface.co/twieland/MIX4_ja-en_helsinki
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-mix_english_vietnamese_4m_en.md b/docs/_posts/ahmedlone127/2024-09-08-mix_english_vietnamese_4m_en.md
new file mode 100644
index 00000000000000..ef5f17dc1a1056
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-mix_english_vietnamese_4m_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mix_english_vietnamese_4m MarianTransformer from Eugenememe
+author: John Snow Labs
+name: mix_english_vietnamese_4m
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mix_english_vietnamese_4m` is a English model originally trained by Eugenememe.
+
+{:.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/mix_english_vietnamese_4m_en_5.5.0_3.0_1725795024209.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mix_english_vietnamese_4m_en_5.5.0_3.0_1725795024209.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("mix_english_vietnamese_4m","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("mix_english_vietnamese_4m","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mix_english_vietnamese_4m|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|475.6 MB|
+
+## References
+
+https://huggingface.co/Eugenememe/mix-en-vi-4m
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-mlm_distilbert_base_uncased_finetuned_game_titles_accelerate_en.md b/docs/_posts/ahmedlone127/2024-09-08-mlm_distilbert_base_uncased_finetuned_game_titles_accelerate_en.md
new file mode 100644
index 00000000000000..5ddc97aa2ccd04
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-mlm_distilbert_base_uncased_finetuned_game_titles_accelerate_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mlm_distilbert_base_uncased_finetuned_game_titles_accelerate DistilBertEmbeddings from kaiku03
+author: John Snow Labs
+name: mlm_distilbert_base_uncased_finetuned_game_titles_accelerate
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mlm_distilbert_base_uncased_finetuned_game_titles_accelerate` is a English model originally trained by kaiku03.
+
+{:.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/mlm_distilbert_base_uncased_finetuned_game_titles_accelerate_en_5.5.0_3.0_1725782786548.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mlm_distilbert_base_uncased_finetuned_game_titles_accelerate_en_5.5.0_3.0_1725782786548.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("mlm_distilbert_base_uncased_finetuned_game_titles_accelerate","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("mlm_distilbert_base_uncased_finetuned_game_titles_accelerate","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mlm_distilbert_base_uncased_finetuned_game_titles_accelerate|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/kaiku03/MLM-distilbert-base-uncased-finetuned-game_titles_accelerate
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-mminilm_l6_v2_english_portuguese_msmarco_v2_pipeline_pt.md b/docs/_posts/ahmedlone127/2024-09-08-mminilm_l6_v2_english_portuguese_msmarco_v2_pipeline_pt.md
new file mode 100644
index 00000000000000..996200e39d184d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-mminilm_l6_v2_english_portuguese_msmarco_v2_pipeline_pt.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Portuguese mminilm_l6_v2_english_portuguese_msmarco_v2_pipeline pipeline XlmRoBertaForSequenceClassification from unicamp-dl
+author: John Snow Labs
+name: mminilm_l6_v2_english_portuguese_msmarco_v2_pipeline
+date: 2024-09-08
+tags: [pt, open_source, pipeline, onnx]
+task: Text Classification
+language: pt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mminilm_l6_v2_english_portuguese_msmarco_v2_pipeline` is a Portuguese model originally trained by unicamp-dl.
+
+{:.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/mminilm_l6_v2_english_portuguese_msmarco_v2_pipeline_pt_5.5.0_3.0_1725800078311.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mminilm_l6_v2_english_portuguese_msmarco_v2_pipeline_pt_5.5.0_3.0_1725800078311.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
+
+pipeline = PretrainedPipeline("mminilm_l6_v2_english_portuguese_msmarco_v2_pipeline", lang = "pt")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mminilm_l6_v2_english_portuguese_msmarco_v2_pipeline", lang = "pt")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mminilm_l6_v2_english_portuguese_msmarco_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|pt|
+|Size:|340.3 MB|
+
+## References
+
+https://huggingface.co/unicamp-dl/mMiniLM-L6-v2-en-pt-msmarco-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-mminilm_l6_v2_english_portuguese_msmarco_v2_pt.md b/docs/_posts/ahmedlone127/2024-09-08-mminilm_l6_v2_english_portuguese_msmarco_v2_pt.md
new file mode 100644
index 00000000000000..ed7d3fbf96f263
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-mminilm_l6_v2_english_portuguese_msmarco_v2_pt.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Portuguese mminilm_l6_v2_english_portuguese_msmarco_v2 XlmRoBertaForSequenceClassification from unicamp-dl
+author: John Snow Labs
+name: mminilm_l6_v2_english_portuguese_msmarco_v2
+date: 2024-09-08
+tags: [pt, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: pt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mminilm_l6_v2_english_portuguese_msmarco_v2` is a Portuguese model originally trained by unicamp-dl.
+
+{:.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/mminilm_l6_v2_english_portuguese_msmarco_v2_pt_5.5.0_3.0_1725800059296.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mminilm_l6_v2_english_portuguese_msmarco_v2_pt_5.5.0_3.0_1725800059296.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("mminilm_l6_v2_english_portuguese_msmarco_v2","pt") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("mminilm_l6_v2_english_portuguese_msmarco_v2", "pt")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mminilm_l6_v2_english_portuguese_msmarco_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|pt|
+|Size:|340.3 MB|
+
+## References
+
+https://huggingface.co/unicamp-dl/mMiniLM-L6-v2-en-pt-msmarco-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-mnli_microsoft_deberta_v3_base_seed_3_en.md b/docs/_posts/ahmedlone127/2024-09-08-mnli_microsoft_deberta_v3_base_seed_3_en.md
new file mode 100644
index 00000000000000..b19be512222b0f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-mnli_microsoft_deberta_v3_base_seed_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mnli_microsoft_deberta_v3_base_seed_3 DeBertaForSequenceClassification from utahnlp
+author: John Snow Labs
+name: mnli_microsoft_deberta_v3_base_seed_3
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mnli_microsoft_deberta_v3_base_seed_3` is a English model originally trained by utahnlp.
+
+{:.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/mnli_microsoft_deberta_v3_base_seed_3_en_5.5.0_3.0_1725812496759.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mnli_microsoft_deberta_v3_base_seed_3_en_5.5.0_3.0_1725812496759.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("mnli_microsoft_deberta_v3_base_seed_3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mnli_microsoft_deberta_v3_base_seed_3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mnli_microsoft_deberta_v3_base_seed_3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|641.2 MB|
+
+## References
+
+https://huggingface.co/utahnlp/mnli_microsoft_deberta-v3-base_seed-3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-mnli_microsoft_deberta_v3_base_seed_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-mnli_microsoft_deberta_v3_base_seed_3_pipeline_en.md
new file mode 100644
index 00000000000000..91fcbdcf8d13fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-mnli_microsoft_deberta_v3_base_seed_3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mnli_microsoft_deberta_v3_base_seed_3_pipeline pipeline DeBertaForSequenceClassification from utahnlp
+author: John Snow Labs
+name: mnli_microsoft_deberta_v3_base_seed_3_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mnli_microsoft_deberta_v3_base_seed_3_pipeline` is a English model originally trained by utahnlp.
+
+{:.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/mnli_microsoft_deberta_v3_base_seed_3_pipeline_en_5.5.0_3.0_1725812559047.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mnli_microsoft_deberta_v3_base_seed_3_pipeline_en_5.5.0_3.0_1725812559047.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
+
+pipeline = PretrainedPipeline("mnli_microsoft_deberta_v3_base_seed_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mnli_microsoft_deberta_v3_base_seed_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mnli_microsoft_deberta_v3_base_seed_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|641.2 MB|
+
+## References
+
+https://huggingface.co/utahnlp/mnli_microsoft_deberta-v3-base_seed-3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-mobilebert_sql_injection_detect_en.md b/docs/_posts/ahmedlone127/2024-09-08-mobilebert_sql_injection_detect_en.md
new file mode 100644
index 00000000000000..69e68928791e9a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-mobilebert_sql_injection_detect_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mobilebert_sql_injection_detect BertForSequenceClassification from cssupport
+author: John Snow Labs
+name: mobilebert_sql_injection_detect
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mobilebert_sql_injection_detect` is a English model originally trained by cssupport.
+
+{:.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/mobilebert_sql_injection_detect_en_5.5.0_3.0_1725768139785.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mobilebert_sql_injection_detect_en_5.5.0_3.0_1725768139785.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("mobilebert_sql_injection_detect","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("mobilebert_sql_injection_detect", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mobilebert_sql_injection_detect|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|92.5 MB|
+
+## References
+
+https://huggingface.co/cssupport/mobilebert-sql-injection-detect
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-model_3_epochs_norwegian_perturb_en.md b/docs/_posts/ahmedlone127/2024-09-08-model_3_epochs_norwegian_perturb_en.md
new file mode 100644
index 00000000000000..9a7a946a4bb19a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-model_3_epochs_norwegian_perturb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English model_3_epochs_norwegian_perturb DistilBertForTokenClassification from cria111
+author: John Snow Labs
+name: model_3_epochs_norwegian_perturb
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_3_epochs_norwegian_perturb` is a English model originally trained by cria111.
+
+{:.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/model_3_epochs_norwegian_perturb_en_5.5.0_3.0_1725837387244.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_3_epochs_norwegian_perturb_en_5.5.0_3.0_1725837387244.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("model_3_epochs_norwegian_perturb","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("model_3_epochs_norwegian_perturb", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_3_epochs_norwegian_perturb|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/cria111/model_3_epochs_no_perturb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-model_qa_5_epoch_russian_en.md b/docs/_posts/ahmedlone127/2024-09-08-model_qa_5_epoch_russian_en.md
new file mode 100644
index 00000000000000..63757087dd0c87
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-model_qa_5_epoch_russian_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English model_qa_5_epoch_russian DistilBertForQuestionAnswering from BramlyReed
+author: John Snow Labs
+name: model_qa_5_epoch_russian
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_qa_5_epoch_russian` is a English model originally trained by BramlyReed.
+
+{:.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/model_qa_5_epoch_russian_en_5.5.0_3.0_1725818578986.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_qa_5_epoch_russian_en_5.5.0_3.0_1725818578986.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("model_qa_5_epoch_russian","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("model_qa_5_epoch_russian", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_qa_5_epoch_russian|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/BramlyReed/model-QA-5-epoch-RU
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-model_qa_5_epoch_russian_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-model_qa_5_epoch_russian_pipeline_en.md
new file mode 100644
index 00000000000000..3f2e7147b7f6db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-model_qa_5_epoch_russian_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English model_qa_5_epoch_russian_pipeline pipeline DistilBertForQuestionAnswering from BramlyReed
+author: John Snow Labs
+name: model_qa_5_epoch_russian_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_qa_5_epoch_russian_pipeline` is a English model originally trained by BramlyReed.
+
+{:.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/model_qa_5_epoch_russian_pipeline_en_5.5.0_3.0_1725818604895.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_qa_5_epoch_russian_pipeline_en_5.5.0_3.0_1725818604895.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
+
+pipeline = PretrainedPipeline("model_qa_5_epoch_russian_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("model_qa_5_epoch_russian_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|model_qa_5_epoch_russian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|505.4 MB|
+
+## References
+
+https://huggingface.co/BramlyReed/model-QA-5-epoch-RU
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-modeldistilbertmaskfinetunedimdb_en.md b/docs/_posts/ahmedlone127/2024-09-08-modeldistilbertmaskfinetunedimdb_en.md
new file mode 100644
index 00000000000000..60129628cff537
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-modeldistilbertmaskfinetunedimdb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English modeldistilbertmaskfinetunedimdb DistilBertEmbeddings from jayspring
+author: John Snow Labs
+name: modeldistilbertmaskfinetunedimdb
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`modeldistilbertmaskfinetunedimdb` is a English model originally trained by jayspring.
+
+{:.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/modeldistilbertmaskfinetunedimdb_en_5.5.0_3.0_1725828679412.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/modeldistilbertmaskfinetunedimdb_en_5.5.0_3.0_1725828679412.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("modeldistilbertmaskfinetunedimdb","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("modeldistilbertmaskfinetunedimdb","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|modeldistilbertmaskfinetunedimdb|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/jayspring/ModelDistilBertMaskFineTunedImdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-mpnet_base_nli_matryoshka_v2_en.md b/docs/_posts/ahmedlone127/2024-09-08-mpnet_base_nli_matryoshka_v2_en.md
new file mode 100644
index 00000000000000..87077f6d83e460
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-mpnet_base_nli_matryoshka_v2_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mpnet_base_nli_matryoshka_v2 MPNetEmbeddings from yoshinori-sano
+author: John Snow Labs
+name: mpnet_base_nli_matryoshka_v2
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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_base_nli_matryoshka_v2` is a English model originally trained by yoshinori-sano.
+
+{:.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_base_nli_matryoshka_v2_en_5.5.0_3.0_1725769967700.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_base_nli_matryoshka_v2_en_5.5.0_3.0_1725769967700.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("mpnet_base_nli_matryoshka_v2","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("mpnet_base_nli_matryoshka_v2","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnet_base_nli_matryoshka_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|404.6 MB|
+
+## References
+
+https://huggingface.co/yoshinori-sano/mpnet-base-nli-matryoshka-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-mpnet_base_nli_matryoshka_yoshinori_sano_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-mpnet_base_nli_matryoshka_yoshinori_sano_pipeline_en.md
new file mode 100644
index 00000000000000..6993f768f4f769
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-mpnet_base_nli_matryoshka_yoshinori_sano_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mpnet_base_nli_matryoshka_yoshinori_sano_pipeline pipeline MPNetEmbeddings from yoshinori-sano
+author: John Snow Labs
+name: mpnet_base_nli_matryoshka_yoshinori_sano_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_base_nli_matryoshka_yoshinori_sano_pipeline` is a English model originally trained by yoshinori-sano.
+
+{:.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_base_nli_matryoshka_yoshinori_sano_pipeline_en_5.5.0_3.0_1725769641939.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_base_nli_matryoshka_yoshinori_sano_pipeline_en_5.5.0_3.0_1725769641939.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
+
+pipeline = PretrainedPipeline("mpnet_base_nli_matryoshka_yoshinori_sano_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mpnet_base_nli_matryoshka_yoshinori_sano_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnet_base_nli_matryoshka_yoshinori_sano_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|404.2 MB|
+
+## References
+
+https://huggingface.co/yoshinori-sano/mpnet-base-nli-matryoshka
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-mpnet_base_trained_on_sts_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-mpnet_base_trained_on_sts_pipeline_en.md
new file mode 100644
index 00000000000000..713568c1bb7d7e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-mpnet_base_trained_on_sts_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mpnet_base_trained_on_sts_pipeline pipeline MPNetEmbeddings from Charul1223
+author: John Snow Labs
+name: mpnet_base_trained_on_sts_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_base_trained_on_sts_pipeline` is a English model originally trained by Charul1223.
+
+{:.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_base_trained_on_sts_pipeline_en_5.5.0_3.0_1725815554189.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_base_trained_on_sts_pipeline_en_5.5.0_3.0_1725815554189.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
+
+pipeline = PretrainedPipeline("mpnet_base_trained_on_sts_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mpnet_base_trained_on_sts_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnet_base_trained_on_sts_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|392.7 MB|
+
+## References
+
+https://huggingface.co/Charul1223/mpnet-base-trained-on-sts
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-mpnet_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-08-mpnet_finetuned_en.md
new file mode 100644
index 00000000000000..35a85f1a268952
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-mpnet_finetuned_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mpnet_finetuned MPNetEmbeddings from aakku
+author: John Snow Labs
+name: mpnet_finetuned
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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_finetuned` is a English model originally trained by aakku.
+
+{:.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_finetuned_en_5.5.0_3.0_1725769051468.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_finetuned_en_5.5.0_3.0_1725769051468.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("mpnet_finetuned","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("mpnet_finetuned","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnet_finetuned|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/aakku/mpnet-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-mpnet_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-mpnet_finetuned_pipeline_en.md
new file mode 100644
index 00000000000000..3418d5968fe3bd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-mpnet_finetuned_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mpnet_finetuned_pipeline pipeline MPNetEmbeddings from aakku
+author: John Snow Labs
+name: mpnet_finetuned_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_finetuned_pipeline` is a English model originally trained by aakku.
+
+{:.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_finetuned_pipeline_en_5.5.0_3.0_1725769073969.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_finetuned_pipeline_en_5.5.0_3.0_1725769073969.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
+
+pipeline = PretrainedPipeline("mpnet_finetuned_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mpnet_finetuned_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnet_finetuned_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/aakku/mpnet-finetuned
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-mpnet_frozen_newtriplets_v2_lr_2e_7_m_5_e_3_en.md b/docs/_posts/ahmedlone127/2024-09-08-mpnet_frozen_newtriplets_v2_lr_2e_7_m_5_e_3_en.md
new file mode 100644
index 00000000000000..e9f5bffefab681
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-mpnet_frozen_newtriplets_v2_lr_2e_7_m_5_e_3_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mpnet_frozen_newtriplets_v2_lr_2e_7_m_5_e_3 MPNetEmbeddings from luiz-and-robert-thesis
+author: John Snow Labs
+name: mpnet_frozen_newtriplets_v2_lr_2e_7_m_5_e_3
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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_frozen_newtriplets_v2_lr_2e_7_m_5_e_3` is a English model originally trained by luiz-and-robert-thesis.
+
+{:.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_frozen_newtriplets_v2_lr_2e_7_m_5_e_3_en_5.5.0_3.0_1725817120755.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_frozen_newtriplets_v2_lr_2e_7_m_5_e_3_en_5.5.0_3.0_1725817120755.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("mpnet_frozen_newtriplets_v2_lr_2e_7_m_5_e_3","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("mpnet_frozen_newtriplets_v2_lr_2e_7_m_5_e_3","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnet_frozen_newtriplets_v2_lr_2e_7_m_5_e_3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/luiz-and-robert-thesis/mpnet-frozen-newtriplets-v2-lr-2e-7-m-5-e-3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-mpnet_model_en.md b/docs/_posts/ahmedlone127/2024-09-08-mpnet_model_en.md
new file mode 100644
index 00000000000000..37be531d2c1134
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-mpnet_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mpnet_model MPNetEmbeddings from CarloSgara
+author: John Snow Labs
+name: mpnet_model
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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_model` is a English model originally trained by CarloSgara.
+
+{:.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_model_en_5.5.0_3.0_1725815922191.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_model_en_5.5.0_3.0_1725815922191.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("mpnet_model","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("mpnet_model","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnet_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/CarloSgara/mpnet_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-mpnet_twitter_freq100_en.md b/docs/_posts/ahmedlone127/2024-09-08-mpnet_twitter_freq100_en.md
new file mode 100644
index 00000000000000..a27e4a4bc60fb4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-mpnet_twitter_freq100_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mpnet_twitter_freq100 MPNetEmbeddings from navidmadani
+author: John Snow Labs
+name: mpnet_twitter_freq100
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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_twitter_freq100` is a English model originally trained by navidmadani.
+
+{:.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_twitter_freq100_en_5.5.0_3.0_1725769050919.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_twitter_freq100_en_5.5.0_3.0_1725769050919.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("mpnet_twitter_freq100","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("mpnet_twitter_freq100","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnet_twitter_freq100|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/navidmadani/mpnet-twitter-freq100
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-mpnet_xnli_en.md b/docs/_posts/ahmedlone127/2024-09-08-mpnet_xnli_en.md
new file mode 100644
index 00000000000000..fe9f6b68b4c2e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-mpnet_xnli_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mpnet_xnli MPNetEmbeddings from jamescalam
+author: John Snow Labs
+name: mpnet_xnli
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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_xnli` is a English model originally trained by jamescalam.
+
+{:.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_xnli_en_5.5.0_3.0_1725769554020.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_xnli_en_5.5.0_3.0_1725769554020.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("mpnet_xnli","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("mpnet_xnli","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnet_xnli|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.2 MB|
+
+## References
+
+https://huggingface.co/jamescalam/mpnet-xnli
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-multi_qa_mpnet_base_dot_v1_covidqa_search_65_25_v2_1epoch_en.md b/docs/_posts/ahmedlone127/2024-09-08-multi_qa_mpnet_base_dot_v1_covidqa_search_65_25_v2_1epoch_en.md
new file mode 100644
index 00000000000000..960231525dc83d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-multi_qa_mpnet_base_dot_v1_covidqa_search_65_25_v2_1epoch_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English multi_qa_mpnet_base_dot_v1_covidqa_search_65_25_v2_1epoch MPNetEmbeddings from checkiejan
+author: John Snow Labs
+name: multi_qa_mpnet_base_dot_v1_covidqa_search_65_25_v2_1epoch
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`multi_qa_mpnet_base_dot_v1_covidqa_search_65_25_v2_1epoch` is a English model originally trained by checkiejan.
+
+{:.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/multi_qa_mpnet_base_dot_v1_covidqa_search_65_25_v2_1epoch_en_5.5.0_3.0_1725815660181.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multi_qa_mpnet_base_dot_v1_covidqa_search_65_25_v2_1epoch_en_5.5.0_3.0_1725815660181.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("multi_qa_mpnet_base_dot_v1_covidqa_search_65_25_v2_1epoch","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("multi_qa_mpnet_base_dot_v1_covidqa_search_65_25_v2_1epoch","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multi_qa_mpnet_base_dot_v1_covidqa_search_65_25_v2_1epoch|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/checkiejan/multi-qa-mpnet-base-dot-v1-covidqa-search-65-25-v2-1epoch
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-multi_qa_mpnet_base_dot_v1_deneme_en.md b/docs/_posts/ahmedlone127/2024-09-08-multi_qa_mpnet_base_dot_v1_deneme_en.md
new file mode 100644
index 00000000000000..a6b4a20b2d44ad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-multi_qa_mpnet_base_dot_v1_deneme_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English multi_qa_mpnet_base_dot_v1_deneme MPNetEmbeddings from mustozsarac
+author: John Snow Labs
+name: multi_qa_mpnet_base_dot_v1_deneme
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`multi_qa_mpnet_base_dot_v1_deneme` is a English model originally trained by mustozsarac.
+
+{:.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/multi_qa_mpnet_base_dot_v1_deneme_en_5.5.0_3.0_1725816836565.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multi_qa_mpnet_base_dot_v1_deneme_en_5.5.0_3.0_1725816836565.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("multi_qa_mpnet_base_dot_v1_deneme","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("multi_qa_mpnet_base_dot_v1_deneme","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multi_qa_mpnet_base_dot_v1_deneme|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/mustozsarac/multi-qa-mpnet-base-dot-v1-deneme
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-multi_qa_mpnet_base_dot_v1_fine_tuned_hs_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-multi_qa_mpnet_base_dot_v1_fine_tuned_hs_v2_pipeline_en.md
new file mode 100644
index 00000000000000..23a2b966c75778
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-multi_qa_mpnet_base_dot_v1_fine_tuned_hs_v2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English multi_qa_mpnet_base_dot_v1_fine_tuned_hs_v2_pipeline pipeline MPNetEmbeddings from dgroechel
+author: John Snow Labs
+name: multi_qa_mpnet_base_dot_v1_fine_tuned_hs_v2_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multi_qa_mpnet_base_dot_v1_fine_tuned_hs_v2_pipeline` is a English model originally trained by dgroechel.
+
+{:.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/multi_qa_mpnet_base_dot_v1_fine_tuned_hs_v2_pipeline_en_5.5.0_3.0_1725815423857.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multi_qa_mpnet_base_dot_v1_fine_tuned_hs_v2_pipeline_en_5.5.0_3.0_1725815423857.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
+
+pipeline = PretrainedPipeline("multi_qa_mpnet_base_dot_v1_fine_tuned_hs_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("multi_qa_mpnet_base_dot_v1_fine_tuned_hs_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multi_qa_mpnet_base_dot_v1_fine_tuned_hs_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/dgroechel/multi-qa-mpnet-base-dot-v1-fine-tuned-hs-v2
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-multilingual_distilbert_intent_classification_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-08-multilingual_distilbert_intent_classification_pipeline_xx.md
new file mode 100644
index 00000000000000..90f020667a8a70
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-multilingual_distilbert_intent_classification_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual multilingual_distilbert_intent_classification_pipeline pipeline DistilBertForSequenceClassification from Mukalingam0813
+author: John Snow Labs
+name: multilingual_distilbert_intent_classification_pipeline
+date: 2024-09-08
+tags: [xx, open_source, pipeline, onnx]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilingual_distilbert_intent_classification_pipeline` is a Multilingual model originally trained by Mukalingam0813.
+
+{:.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/multilingual_distilbert_intent_classification_pipeline_xx_5.5.0_3.0_1725764922268.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilingual_distilbert_intent_classification_pipeline_xx_5.5.0_3.0_1725764922268.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
+
+pipeline = PretrainedPipeline("multilingual_distilbert_intent_classification_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("multilingual_distilbert_intent_classification_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multilingual_distilbert_intent_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/Mukalingam0813/multilingual-Distilbert-intent-classification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-multilingual_distilbert_intent_classification_xx.md b/docs/_posts/ahmedlone127/2024-09-08-multilingual_distilbert_intent_classification_xx.md
new file mode 100644
index 00000000000000..69b50092603464
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-multilingual_distilbert_intent_classification_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual multilingual_distilbert_intent_classification DistilBertForSequenceClassification from Mukalingam0813
+author: John Snow Labs
+name: multilingual_distilbert_intent_classification
+date: 2024-09-08
+tags: [xx, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilingual_distilbert_intent_classification` is a Multilingual model originally trained by Mukalingam0813.
+
+{:.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/multilingual_distilbert_intent_classification_xx_5.5.0_3.0_1725764898797.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilingual_distilbert_intent_classification_xx_5.5.0_3.0_1725764898797.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("multilingual_distilbert_intent_classification","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("multilingual_distilbert_intent_classification", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multilingual_distilbert_intent_classification|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|xx|
+|Size:|507.6 MB|
+
+## References
+
+https://huggingface.co/Mukalingam0813/multilingual-Distilbert-intent-classification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-multilingual_sarcasm_detector_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-08-multilingual_sarcasm_detector_pipeline_xx.md
new file mode 100644
index 00000000000000..c350ae022f97bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-multilingual_sarcasm_detector_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual multilingual_sarcasm_detector_pipeline pipeline BertForSequenceClassification from helinivan
+author: John Snow Labs
+name: multilingual_sarcasm_detector_pipeline
+date: 2024-09-08
+tags: [xx, open_source, pipeline, onnx]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilingual_sarcasm_detector_pipeline` is a Multilingual model originally trained by helinivan.
+
+{:.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/multilingual_sarcasm_detector_pipeline_xx_5.5.0_3.0_1725761239743.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilingual_sarcasm_detector_pipeline_xx_5.5.0_3.0_1725761239743.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
+
+pipeline = PretrainedPipeline("multilingual_sarcasm_detector_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("multilingual_sarcasm_detector_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multilingual_sarcasm_detector_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|627.8 MB|
+
+## References
+
+https://huggingface.co/helinivan/multilingual-sarcasm-detector
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-multilingual_xlm_roberta_for_ner_mehmettozlu_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-08-multilingual_xlm_roberta_for_ner_mehmettozlu_pipeline_xx.md
new file mode 100644
index 00000000000000..b86715f87a35e2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-multilingual_xlm_roberta_for_ner_mehmettozlu_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual multilingual_xlm_roberta_for_ner_mehmettozlu_pipeline pipeline XlmRoBertaForTokenClassification from mehmettozlu
+author: John Snow Labs
+name: multilingual_xlm_roberta_for_ner_mehmettozlu_pipeline
+date: 2024-09-08
+tags: [xx, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilingual_xlm_roberta_for_ner_mehmettozlu_pipeline` is a Multilingual model originally trained by mehmettozlu.
+
+{:.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/multilingual_xlm_roberta_for_ner_mehmettozlu_pipeline_xx_5.5.0_3.0_1725784663136.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilingual_xlm_roberta_for_ner_mehmettozlu_pipeline_xx_5.5.0_3.0_1725784663136.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
+
+pipeline = PretrainedPipeline("multilingual_xlm_roberta_for_ner_mehmettozlu_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("multilingual_xlm_roberta_for_ner_mehmettozlu_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multilingual_xlm_roberta_for_ner_mehmettozlu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/mehmettozlu/multilingual-xlm-roberta-for-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-multilingual_xlm_roberta_for_ner_mehmettozlu_xx.md b/docs/_posts/ahmedlone127/2024-09-08-multilingual_xlm_roberta_for_ner_mehmettozlu_xx.md
new file mode 100644
index 00000000000000..f36ee8077d6ca2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-multilingual_xlm_roberta_for_ner_mehmettozlu_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual multilingual_xlm_roberta_for_ner_mehmettozlu XlmRoBertaForTokenClassification from mehmettozlu
+author: John Snow Labs
+name: multilingual_xlm_roberta_for_ner_mehmettozlu
+date: 2024-09-08
+tags: [xx, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilingual_xlm_roberta_for_ner_mehmettozlu` is a Multilingual model originally trained by mehmettozlu.
+
+{:.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/multilingual_xlm_roberta_for_ner_mehmettozlu_xx_5.5.0_3.0_1725784581219.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilingual_xlm_roberta_for_ner_mehmettozlu_xx_5.5.0_3.0_1725784581219.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("multilingual_xlm_roberta_for_ner_mehmettozlu","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("multilingual_xlm_roberta_for_ner_mehmettozlu", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multilingual_xlm_roberta_for_ner_mehmettozlu|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|xx|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/mehmettozlu/multilingual-xlm-roberta-for-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-multilingual_xlm_roberta_for_ner_ocaklisemih_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-08-multilingual_xlm_roberta_for_ner_ocaklisemih_pipeline_xx.md
new file mode 100644
index 00000000000000..734dd44498820a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-multilingual_xlm_roberta_for_ner_ocaklisemih_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual multilingual_xlm_roberta_for_ner_ocaklisemih_pipeline pipeline XlmRoBertaForTokenClassification from ocaklisemih
+author: John Snow Labs
+name: multilingual_xlm_roberta_for_ner_ocaklisemih_pipeline
+date: 2024-09-08
+tags: [xx, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilingual_xlm_roberta_for_ner_ocaklisemih_pipeline` is a Multilingual model originally trained by ocaklisemih.
+
+{:.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/multilingual_xlm_roberta_for_ner_ocaklisemih_pipeline_xx_5.5.0_3.0_1725807786274.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilingual_xlm_roberta_for_ner_ocaklisemih_pipeline_xx_5.5.0_3.0_1725807786274.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
+
+pipeline = PretrainedPipeline("multilingual_xlm_roberta_for_ner_ocaklisemih_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("multilingual_xlm_roberta_for_ner_ocaklisemih_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multilingual_xlm_roberta_for_ner_ocaklisemih_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|840.4 MB|
+
+## References
+
+https://huggingface.co/ocaklisemih/multilingual-xlm-roberta-for-ner
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-multiplenegativesrankingloss_20_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-multiplenegativesrankingloss_20_pipeline_en.md
new file mode 100644
index 00000000000000..70deb117a90e7a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-multiplenegativesrankingloss_20_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English multiplenegativesrankingloss_20_pipeline pipeline MPNetEmbeddings from marianodo
+author: John Snow Labs
+name: multiplenegativesrankingloss_20_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multiplenegativesrankingloss_20_pipeline` is a English model originally trained by marianodo.
+
+{:.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/multiplenegativesrankingloss_20_pipeline_en_5.5.0_3.0_1725817008752.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multiplenegativesrankingloss_20_pipeline_en_5.5.0_3.0_1725817008752.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
+
+pipeline = PretrainedPipeline("multiplenegativesrankingloss_20_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("multiplenegativesrankingloss_20_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|multiplenegativesrankingloss_20_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/marianodo/MultipleNegativesRankingLoss-20
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-n_distilbert_imdb_padding100model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-n_distilbert_imdb_padding100model_pipeline_en.md
new file mode 100644
index 00000000000000..8a930159d6df08
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-n_distilbert_imdb_padding100model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English n_distilbert_imdb_padding100model_pipeline pipeline DistilBertForSequenceClassification from Realgon
+author: John Snow Labs
+name: n_distilbert_imdb_padding100model_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`n_distilbert_imdb_padding100model_pipeline` is a English model originally trained by Realgon.
+
+{:.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/n_distilbert_imdb_padding100model_pipeline_en_5.5.0_3.0_1725808936232.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/n_distilbert_imdb_padding100model_pipeline_en_5.5.0_3.0_1725808936232.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
+
+pipeline = PretrainedPipeline("n_distilbert_imdb_padding100model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("n_distilbert_imdb_padding100model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|n_distilbert_imdb_padding100model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.8 MB|
+
+## References
+
+https://huggingface.co/Realgon/N_distilbert_imdb_padding100model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-n_distilbert_twitterfin_padding40model_en.md b/docs/_posts/ahmedlone127/2024-09-08-n_distilbert_twitterfin_padding40model_en.md
new file mode 100644
index 00000000000000..f514a97c16921d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-n_distilbert_twitterfin_padding40model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English n_distilbert_twitterfin_padding40model DistilBertForSequenceClassification from Realgon
+author: John Snow Labs
+name: n_distilbert_twitterfin_padding40model
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`n_distilbert_twitterfin_padding40model` is a English model originally trained by Realgon.
+
+{:.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/n_distilbert_twitterfin_padding40model_en_5.5.0_3.0_1725776853901.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/n_distilbert_twitterfin_padding40model_en_5.5.0_3.0_1725776853901.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("n_distilbert_twitterfin_padding40model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("n_distilbert_twitterfin_padding40model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|n_distilbert_twitterfin_padding40model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.6 MB|
+
+## References
+
+https://huggingface.co/Realgon/N_distilbert_twitterfin_padding40model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-nepal_bhasa_ai_oriya_humantext_categorisation_en.md b/docs/_posts/ahmedlone127/2024-09-08-nepal_bhasa_ai_oriya_humantext_categorisation_en.md
new file mode 100644
index 00000000000000..c55116f48d6103
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-nepal_bhasa_ai_oriya_humantext_categorisation_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English nepal_bhasa_ai_oriya_humantext_categorisation BertForSequenceClassification from priyabrat
+author: John Snow Labs
+name: nepal_bhasa_ai_oriya_humantext_categorisation
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nepal_bhasa_ai_oriya_humantext_categorisation` is a English model originally trained by priyabrat.
+
+{:.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/nepal_bhasa_ai_oriya_humantext_categorisation_en_5.5.0_3.0_1725768259014.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nepal_bhasa_ai_oriya_humantext_categorisation_en_5.5.0_3.0_1725768259014.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("nepal_bhasa_ai_oriya_humantext_categorisation","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("nepal_bhasa_ai_oriya_humantext_categorisation", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nepal_bhasa_ai_oriya_humantext_categorisation|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/priyabrat/New_AI_or_Humantext_categorisation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-ner_model_dannyleo16_en.md b/docs/_posts/ahmedlone127/2024-09-08-ner_model_dannyleo16_en.md
new file mode 100644
index 00000000000000..731f4e6316cd8a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-ner_model_dannyleo16_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_model_dannyleo16 DistilBertForTokenClassification from dannyLeo16
+author: John Snow Labs
+name: ner_model_dannyleo16
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_model_dannyleo16` is a English model originally trained by dannyLeo16.
+
+{:.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/ner_model_dannyleo16_en_5.5.0_3.0_1725827929863.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_model_dannyleo16_en_5.5.0_3.0_1725827929863.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("ner_model_dannyleo16","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("ner_model_dannyleo16", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_model_dannyleo16|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|250.3 MB|
+
+## References
+
+https://huggingface.co/dannyLeo16/ner_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-ner_model_wizardofchance_en.md b/docs/_posts/ahmedlone127/2024-09-08-ner_model_wizardofchance_en.md
new file mode 100644
index 00000000000000..b39d83de7b7d78
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-ner_model_wizardofchance_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_model_wizardofchance DistilBertForTokenClassification from wizardofchance
+author: John Snow Labs
+name: ner_model_wizardofchance
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_model_wizardofchance` is a English model originally trained by wizardofchance.
+
+{:.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/ner_model_wizardofchance_en_5.5.0_3.0_1725788824769.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_model_wizardofchance_en_5.5.0_3.0_1725788824769.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("ner_model_wizardofchance","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("ner_model_wizardofchance", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_model_wizardofchance|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/wizardofchance/ner-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-ner_multilingualbert_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-08-ner_multilingualbert_pipeline_xx.md
new file mode 100644
index 00000000000000..ffb28a823b5464
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-ner_multilingualbert_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual ner_multilingualbert_pipeline pipeline BertForTokenClassification from DrRinS
+author: John Snow Labs
+name: ner_multilingualbert_pipeline
+date: 2024-09-08
+tags: [xx, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_multilingualbert_pipeline` is a Multilingual model originally trained by DrRinS.
+
+{:.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/ner_multilingualbert_pipeline_xx_5.5.0_3.0_1725834782758.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_multilingualbert_pipeline_xx_5.5.0_3.0_1725834782758.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
+
+pipeline = PretrainedPipeline("ner_multilingualbert_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_multilingualbert_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_multilingualbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/DrRinS/NER_MultilingualBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-ner_named_entity_recgnition_en.md b/docs/_posts/ahmedlone127/2024-09-08-ner_named_entity_recgnition_en.md
new file mode 100644
index 00000000000000..2bbfb17efc1ec1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-ner_named_entity_recgnition_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ner_named_entity_recgnition DistilBertForTokenClassification from Mohamedfasil
+author: John Snow Labs
+name: ner_named_entity_recgnition
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_named_entity_recgnition` is a English model originally trained by Mohamedfasil.
+
+{:.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/ner_named_entity_recgnition_en_5.5.0_3.0_1725827689559.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_named_entity_recgnition_en_5.5.0_3.0_1725827689559.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("ner_named_entity_recgnition","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("ner_named_entity_recgnition", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_named_entity_recgnition|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Mohamedfasil/ner-named-entity-recgnition
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-ner_named_entity_recgnition_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-ner_named_entity_recgnition_pipeline_en.md
new file mode 100644
index 00000000000000..6f2a4c9e109a82
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-ner_named_entity_recgnition_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English ner_named_entity_recgnition_pipeline pipeline DistilBertForTokenClassification from Mohamedfasil
+author: John Snow Labs
+name: ner_named_entity_recgnition_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_named_entity_recgnition_pipeline` is a English model originally trained by Mohamedfasil.
+
+{:.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/ner_named_entity_recgnition_pipeline_en_5.5.0_3.0_1725827701571.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_named_entity_recgnition_pipeline_en_5.5.0_3.0_1725827701571.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
+
+pipeline = PretrainedPipeline("ner_named_entity_recgnition_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ner_named_entity_recgnition_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ner_named_entity_recgnition_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Mohamedfasil/ner-named-entity-recgnition
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-nid_turkish_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-nid_turkish_pipeline_en.md
new file mode 100644
index 00000000000000..e147b388ec110d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-nid_turkish_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English nid_turkish_pipeline pipeline DistilBertForSequenceClassification from mwz
+author: John Snow Labs
+name: nid_turkish_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nid_turkish_pipeline` is a English model originally trained by mwz.
+
+{:.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/nid_turkish_pipeline_en_5.5.0_3.0_1725808410451.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nid_turkish_pipeline_en_5.5.0_3.0_1725808410451.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
+
+pipeline = PretrainedPipeline("nid_turkish_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nid_turkish_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nid_turkish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|246.1 MB|
+
+## References
+
+https://huggingface.co/mwz/NID_tr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-nyfin_en.md b/docs/_posts/ahmedlone127/2024-09-08-nyfin_en.md
new file mode 100644
index 00000000000000..bd5972598811c8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-nyfin_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English nyfin DistilBertForQuestionAnswering from kevinbram
+author: John Snow Labs
+name: nyfin
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nyfin` is a English model originally trained by kevinbram.
+
+{:.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/nyfin_en_5.5.0_3.0_1725818115340.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nyfin_en_5.5.0_3.0_1725818115340.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("nyfin","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("nyfin", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nyfin|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/kevinbram/nyfin
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-nyfin_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-nyfin_pipeline_en.md
new file mode 100644
index 00000000000000..75f27bac59258d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-nyfin_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English nyfin_pipeline pipeline DistilBertForQuestionAnswering from kevinbram
+author: John Snow Labs
+name: nyfin_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nyfin_pipeline` is a English model originally trained by kevinbram.
+
+{:.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/nyfin_pipeline_en_5.5.0_3.0_1725818127935.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nyfin_pipeline_en_5.5.0_3.0_1725818127935.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
+
+pipeline = PretrainedPipeline("nyfin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nyfin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nyfin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/kevinbram/nyfin
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-open_gpt_3_5_detector_en.md b/docs/_posts/ahmedlone127/2024-09-08-open_gpt_3_5_detector_en.md
new file mode 100644
index 00000000000000..356254227a09b1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-open_gpt_3_5_detector_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English open_gpt_3_5_detector DistilBertForSequenceClassification from nothingiisreal
+author: John Snow Labs
+name: open_gpt_3_5_detector
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`open_gpt_3_5_detector` is a English model originally trained by nothingiisreal.
+
+{:.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/open_gpt_3_5_detector_en_5.5.0_3.0_1725808596965.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/open_gpt_3_5_detector_en_5.5.0_3.0_1725808596965.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("open_gpt_3_5_detector","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("open_gpt_3_5_detector", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|open_gpt_3_5_detector|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/nothingiisreal/open-gpt-3.5-detector
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-open_gpt_3_5_detector_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-open_gpt_3_5_detector_pipeline_en.md
new file mode 100644
index 00000000000000..3277293134bc95
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-open_gpt_3_5_detector_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English open_gpt_3_5_detector_pipeline pipeline DistilBertForSequenceClassification from nothingiisreal
+author: John Snow Labs
+name: open_gpt_3_5_detector_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`open_gpt_3_5_detector_pipeline` is a English model originally trained by nothingiisreal.
+
+{:.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/open_gpt_3_5_detector_pipeline_en_5.5.0_3.0_1725808610371.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/open_gpt_3_5_detector_pipeline_en_5.5.0_3.0_1725808610371.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
+
+pipeline = PretrainedPipeline("open_gpt_3_5_detector_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("open_gpt_3_5_detector_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|open_gpt_3_5_detector_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/nothingiisreal/open-gpt-3.5-detector
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_base_lsp_simple_wce_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_base_lsp_simple_wce_en.md
new file mode 100644
index 00000000000000..a09c9dea76f2d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_base_lsp_simple_wce_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_base_lsp_simple_wce MarianTransformer from ethansimrm
+author: John Snow Labs
+name: opus_base_lsp_simple_wce
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_base_lsp_simple_wce` is a English model originally trained by ethansimrm.
+
+{:.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/opus_base_lsp_simple_wce_en_5.5.0_3.0_1725796361821.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_base_lsp_simple_wce_en_5.5.0_3.0_1725796361821.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_base_lsp_simple_wce","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_base_lsp_simple_wce","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_base_lsp_simple_wce|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.4 MB|
+
+## References
+
+https://huggingface.co/ethansimrm/opus_base_lsp_simple_wce
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_big_aon_freq_wce_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_big_aon_freq_wce_en.md
new file mode 100644
index 00000000000000..8dbf37c06c68ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_big_aon_freq_wce_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_big_aon_freq_wce MarianTransformer from ethansimrm
+author: John Snow Labs
+name: opus_big_aon_freq_wce
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_big_aon_freq_wce` is a English model originally trained by ethansimrm.
+
+{:.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/opus_big_aon_freq_wce_en_5.5.0_3.0_1725795620724.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_big_aon_freq_wce_en_5.5.0_3.0_1725795620724.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_big_aon_freq_wce","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_big_aon_freq_wce","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_big_aon_freq_wce|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/ethansimrm/opus_big_AoN_freq_wce
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_em_deberta_large_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_em_deberta_large_en.md
new file mode 100644
index 00000000000000..f663871de75f47
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_em_deberta_large_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_em_deberta_large DeBertaForSequenceClassification from kerpr
+author: John Snow Labs
+name: opus_em_deberta_large
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_em_deberta_large` is a English model originally trained by kerpr.
+
+{:.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/opus_em_deberta_large_en_5.5.0_3.0_1725811524279.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_em_deberta_large_en_5.5.0_3.0_1725811524279.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("opus_em_deberta_large","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("opus_em_deberta_large", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_em_deberta_large|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/kerpr/opus-em-deberta-large
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_chinese_german_tuned_tatoeba_small_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_chinese_german_tuned_tatoeba_small_en.md
new file mode 100644
index 00000000000000..235e59bed8ec17
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_chinese_german_tuned_tatoeba_small_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_chinese_german_tuned_tatoeba_small MarianTransformer from ykliu1892
+author: John Snow Labs
+name: opus_maltese_chinese_german_tuned_tatoeba_small
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_chinese_german_tuned_tatoeba_small` is a English model originally trained by ykliu1892.
+
+{:.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/opus_maltese_chinese_german_tuned_tatoeba_small_en_5.5.0_3.0_1725796008441.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_chinese_german_tuned_tatoeba_small_en_5.5.0_3.0_1725796008441.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_chinese_german_tuned_tatoeba_small","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_chinese_german_tuned_tatoeba_small","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_chinese_german_tuned_tatoeba_small|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|541.0 MB|
+
+## References
+
+https://huggingface.co/ykliu1892/opus-mt-zh-de-tuned-Tatoeba-small
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_2000instancesopus_leaningrate2e_05_batchsize8_11epoch_3_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_2000instancesopus_leaningrate2e_05_batchsize8_11epoch_3_en.md
new file mode 100644
index 00000000000000..e4665ca127515b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_2000instancesopus_leaningrate2e_05_batchsize8_11epoch_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_2000instancesopus_leaningrate2e_05_batchsize8_11epoch_3 MarianTransformer from meghazisofiane
+author: John Snow Labs
+name: opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_2000instancesopus_leaningrate2e_05_batchsize8_11epoch_3
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_2000instancesopus_leaningrate2e_05_batchsize8_11epoch_3` is a English model originally trained by meghazisofiane.
+
+{:.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/opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_2000instancesopus_leaningrate2e_05_batchsize8_11epoch_3_en_5.5.0_3.0_1725766102379.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_2000instancesopus_leaningrate2e_05_batchsize8_11epoch_3_en_5.5.0_3.0_1725766102379.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_2000instancesopus_leaningrate2e_05_batchsize8_11epoch_3","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_2000instancesopus_leaningrate2e_05_batchsize8_11epoch_3","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_2000instancesopus_leaningrate2e_05_batchsize8_11epoch_3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|528.2 MB|
+
+## References
+
+https://huggingface.co/meghazisofiane/opus-mt-en-ar-evaluated-en-to-ar-2000instancesopus-leaningRate2e-05-batchSize8-11epoch-3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_4000instances_un_multi_leaningrate2e_05_batchsize8_11_action_1_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_4000instances_un_multi_leaningrate2e_05_batchsize8_11_action_1_en.md
new file mode 100644
index 00000000000000..e391b4c587b173
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_4000instances_un_multi_leaningrate2e_05_batchsize8_11_action_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_4000instances_un_multi_leaningrate2e_05_batchsize8_11_action_1 MarianTransformer from meghazisofiane
+author: John Snow Labs
+name: opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_4000instances_un_multi_leaningrate2e_05_batchsize8_11_action_1
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_4000instances_un_multi_leaningrate2e_05_batchsize8_11_action_1` is a English model originally trained by meghazisofiane.
+
+{:.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/opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_4000instances_un_multi_leaningrate2e_05_batchsize8_11_action_1_en_5.5.0_3.0_1725795579576.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_4000instances_un_multi_leaningrate2e_05_batchsize8_11_action_1_en_5.5.0_3.0_1725795579576.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_4000instances_un_multi_leaningrate2e_05_batchsize8_11_action_1","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_4000instances_un_multi_leaningrate2e_05_batchsize8_11_action_1","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_arabic_evaluated_english_tonga_tonga_islands_arabic_4000instances_un_multi_leaningrate2e_05_batchsize8_11_action_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|528.2 MB|
+
+## References
+
+https://huggingface.co/meghazisofiane/opus-mt-en-ar-evaluated-en-to-ar-4000instances-un_multi-leaningRate2e-05-batchSize8-11-action-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_dutch_finetuned_20k_128_256_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_dutch_finetuned_20k_128_256_en.md
new file mode 100644
index 00000000000000..554e00a8414d2b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_dutch_finetuned_20k_128_256_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_dutch_finetuned_20k_128_256 MarianTransformer from kalcho100
+author: John Snow Labs
+name: opus_maltese_english_dutch_finetuned_20k_128_256
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_dutch_finetuned_20k_128_256` is a English model originally trained by kalcho100.
+
+{:.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/opus_maltese_english_dutch_finetuned_20k_128_256_en_5.5.0_3.0_1725832131132.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_dutch_finetuned_20k_128_256_en_5.5.0_3.0_1725832131132.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_dutch_finetuned_20k_128_256","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_dutch_finetuned_20k_128_256","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_dutch_finetuned_20k_128_256|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|548.6 MB|
+
+## References
+
+https://huggingface.co/kalcho100/opus-mt-en-nl-finetuned_20k_128_256
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_dutch_finetuned_20k_128_256_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_dutch_finetuned_20k_128_256_pipeline_en.md
new file mode 100644
index 00000000000000..fb37bf17173667
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_dutch_finetuned_20k_128_256_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_dutch_finetuned_20k_128_256_pipeline pipeline MarianTransformer from kalcho100
+author: John Snow Labs
+name: opus_maltese_english_dutch_finetuned_20k_128_256_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_dutch_finetuned_20k_128_256_pipeline` is a English model originally trained by kalcho100.
+
+{:.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/opus_maltese_english_dutch_finetuned_20k_128_256_pipeline_en_5.5.0_3.0_1725832160865.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_dutch_finetuned_20k_128_256_pipeline_en_5.5.0_3.0_1725832160865.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
+
+pipeline = PretrainedPipeline("opus_maltese_english_dutch_finetuned_20k_128_256_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_dutch_finetuned_20k_128_256_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_dutch_finetuned_20k_128_256_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|549.1 MB|
+
+## References
+
+https://huggingface.co/kalcho100/opus-mt-en-nl-finetuned_20k_128_256
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_dutch_finetuned_20k_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_dutch_finetuned_20k_en.md
new file mode 100644
index 00000000000000..7a8b0785809662
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_dutch_finetuned_20k_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_dutch_finetuned_20k MarianTransformer from kalcho100
+author: John Snow Labs
+name: opus_maltese_english_dutch_finetuned_20k
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_dutch_finetuned_20k` is a English model originally trained by kalcho100.
+
+{:.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/opus_maltese_english_dutch_finetuned_20k_en_5.5.0_3.0_1725765984575.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_dutch_finetuned_20k_en_5.5.0_3.0_1725765984575.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_dutch_finetuned_20k","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_dutch_finetuned_20k","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_dutch_finetuned_20k|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|548.7 MB|
+
+## References
+
+https://huggingface.co/kalcho100/opus-mt-en-nl-finetuned_20k
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_french_bds_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_french_bds_en.md
new file mode 100644
index 00000000000000..13f2a5257a8035
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_french_bds_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_french_bds MarianTransformer from Anhptp
+author: John Snow Labs
+name: opus_maltese_english_french_bds
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_french_bds` is a English model originally trained by Anhptp.
+
+{:.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/opus_maltese_english_french_bds_en_5.5.0_3.0_1725796310454.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_french_bds_en_5.5.0_3.0_1725796310454.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_french_bds","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_french_bds","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_french_bds|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.4 MB|
+
+## References
+
+https://huggingface.co/Anhptp/opus-mt-en-fr-BDS
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_french_bds_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_french_bds_pipeline_en.md
new file mode 100644
index 00000000000000..7fa0a51bcf1960
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_french_bds_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_french_bds_pipeline pipeline MarianTransformer from Anhptp
+author: John Snow Labs
+name: opus_maltese_english_french_bds_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_french_bds_pipeline` is a English model originally trained by Anhptp.
+
+{:.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/opus_maltese_english_french_bds_pipeline_en_5.5.0_3.0_1725796335391.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_french_bds_pipeline_en_5.5.0_3.0_1725796335391.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
+
+pipeline = PretrainedPipeline("opus_maltese_english_french_bds_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_french_bds_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_french_bds_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|508.9 MB|
+
+## References
+
+https://huggingface.co/Anhptp/opus-mt-en-fr-BDS
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_french_wmt14_english_french_1million_20epochs_v2_pipeline_nan.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_french_wmt14_english_french_1million_20epochs_v2_pipeline_nan.md
new file mode 100644
index 00000000000000..6b992833a8f923
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_french_wmt14_english_french_1million_20epochs_v2_pipeline_nan.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: None opus_maltese_english_french_wmt14_english_french_1million_20epochs_v2_pipeline pipeline MarianTransformer from sriram-sanjeev9s
+author: John Snow Labs
+name: opus_maltese_english_french_wmt14_english_french_1million_20epochs_v2_pipeline
+date: 2024-09-08
+tags: [nan, open_source, pipeline, onnx]
+task: Translation
+language: nan
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_french_wmt14_english_french_1million_20epochs_v2_pipeline` is a None model originally trained by sriram-sanjeev9s.
+
+{:.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/opus_maltese_english_french_wmt14_english_french_1million_20epochs_v2_pipeline_nan_5.5.0_3.0_1725765349182.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_french_wmt14_english_french_1million_20epochs_v2_pipeline_nan_5.5.0_3.0_1725765349182.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
+
+pipeline = PretrainedPipeline("opus_maltese_english_french_wmt14_english_french_1million_20epochs_v2_pipeline", lang = "nan")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_french_wmt14_english_french_1million_20epochs_v2_pipeline", lang = "nan")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_french_wmt14_english_french_1million_20epochs_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|nan|
+|Size:|502.5 MB|
+
+## References
+
+https://huggingface.co/sriram-sanjeev9s/opus-mt-en-fr_wmt14_En_Fr_1million_20epochs_v2
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_ganda_finetuned_english_tonga_tonga_islands_ganda_finetuned_english_tonga_tonga_islands_ganda_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_ganda_finetuned_english_tonga_tonga_islands_ganda_finetuned_english_tonga_tonga_islands_ganda_en.md
new file mode 100644
index 00000000000000..8cbe76e2172173
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_ganda_finetuned_english_tonga_tonga_islands_ganda_finetuned_english_tonga_tonga_islands_ganda_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_ganda_finetuned_english_tonga_tonga_islands_ganda_finetuned_english_tonga_tonga_islands_ganda MarianTransformer from Tobius
+author: John Snow Labs
+name: opus_maltese_english_ganda_finetuned_english_tonga_tonga_islands_ganda_finetuned_english_tonga_tonga_islands_ganda
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_ganda_finetuned_english_tonga_tonga_islands_ganda_finetuned_english_tonga_tonga_islands_ganda` is a English model originally trained by Tobius.
+
+{:.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/opus_maltese_english_ganda_finetuned_english_tonga_tonga_islands_ganda_finetuned_english_tonga_tonga_islands_ganda_en_5.5.0_3.0_1725765698694.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_ganda_finetuned_english_tonga_tonga_islands_ganda_finetuned_english_tonga_tonga_islands_ganda_en_5.5.0_3.0_1725765698694.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_ganda_finetuned_english_tonga_tonga_islands_ganda_finetuned_english_tonga_tonga_islands_ganda","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_ganda_finetuned_english_tonga_tonga_islands_ganda_finetuned_english_tonga_tonga_islands_ganda","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_ganda_finetuned_english_tonga_tonga_islands_ganda_finetuned_english_tonga_tonga_islands_ganda|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|515.1 MB|
+
+## References
+
+https://huggingface.co/Tobius/opus-mt-en-lg-finetuned-en-to-lg-finetuned-en-to-lg
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_ad_iiitd_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_ad_iiitd_pipeline_en.md
new file mode 100644
index 00000000000000..e012426fefd37d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_ad_iiitd_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_ad_iiitd_pipeline pipeline MarianTransformer from AD-IIITD
+author: John Snow Labs
+name: opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_ad_iiitd_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_ad_iiitd_pipeline` is a English model originally trained by AD-IIITD.
+
+{:.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/opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_ad_iiitd_pipeline_en_5.5.0_3.0_1725795514091.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_ad_iiitd_pipeline_en_5.5.0_3.0_1725795514091.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
+
+pipeline = PretrainedPipeline("opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_ad_iiitd_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_ad_iiitd_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_ad_iiitd_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|500.0 MB|
+
+## References
+
+https://huggingface.co/AD-IIITD/opus-mt-en-de-finetuned-en-to-de
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_afreireosorio_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_afreireosorio_en.md
new file mode 100644
index 00000000000000..b4ec5a19307dbf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_afreireosorio_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_afreireosorio MarianTransformer from afreireosorio
+author: John Snow Labs
+name: opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_afreireosorio
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_afreireosorio` is a English model originally trained by afreireosorio.
+
+{:.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/opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_afreireosorio_en_5.5.0_3.0_1725795425759.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_afreireosorio_en_5.5.0_3.0_1725795425759.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_afreireosorio","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_afreireosorio","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_afreireosorio|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|498.1 MB|
+
+## References
+
+https://huggingface.co/afreireosorio/opus-mt-en-de-finetuned-en-to-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_afreireosorio_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_afreireosorio_pipeline_en.md
new file mode 100644
index 00000000000000..406618a7c045e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_afreireosorio_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_afreireosorio_pipeline pipeline MarianTransformer from afreireosorio
+author: John Snow Labs
+name: opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_afreireosorio_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_afreireosorio_pipeline` is a English model originally trained by afreireosorio.
+
+{:.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/opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_afreireosorio_pipeline_en_5.5.0_3.0_1725795449693.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_afreireosorio_pipeline_en_5.5.0_3.0_1725795449693.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
+
+pipeline = PretrainedPipeline("opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_afreireosorio_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_afreireosorio_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_german_finetuned_english_tonga_tonga_islands_german_afreireosorio_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|498.6 MB|
+
+## References
+
+https://huggingface.co/afreireosorio/opus-mt-en-de-finetuned-en-to-de
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_indonesian_ccmatrix_v2_best_loss_bleu_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_indonesian_ccmatrix_v2_best_loss_bleu_en.md
new file mode 100644
index 00000000000000..59f45ebf32badd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_indonesian_ccmatrix_v2_best_loss_bleu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_indonesian_ccmatrix_v2_best_loss_bleu MarianTransformer from yonathanstwn
+author: John Snow Labs
+name: opus_maltese_english_indonesian_ccmatrix_v2_best_loss_bleu
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_indonesian_ccmatrix_v2_best_loss_bleu` is a English model originally trained by yonathanstwn.
+
+{:.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/opus_maltese_english_indonesian_ccmatrix_v2_best_loss_bleu_en_5.5.0_3.0_1725766213257.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_indonesian_ccmatrix_v2_best_loss_bleu_en_5.5.0_3.0_1725766213257.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_indonesian_ccmatrix_v2_best_loss_bleu","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_indonesian_ccmatrix_v2_best_loss_bleu","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_indonesian_ccmatrix_v2_best_loss_bleu|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|481.9 MB|
+
+## References
+
+https://huggingface.co/yonathanstwn/opus-mt-en-id-ccmatrix-v2-best-loss-bleu
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_indonesian_ccmatrix_v2_best_loss_bleu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_indonesian_ccmatrix_v2_best_loss_bleu_pipeline_en.md
new file mode 100644
index 00000000000000..4a348758d00530
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_indonesian_ccmatrix_v2_best_loss_bleu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_indonesian_ccmatrix_v2_best_loss_bleu_pipeline pipeline MarianTransformer from yonathanstwn
+author: John Snow Labs
+name: opus_maltese_english_indonesian_ccmatrix_v2_best_loss_bleu_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_indonesian_ccmatrix_v2_best_loss_bleu_pipeline` is a English model originally trained by yonathanstwn.
+
+{:.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/opus_maltese_english_indonesian_ccmatrix_v2_best_loss_bleu_pipeline_en_5.5.0_3.0_1725766236490.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_indonesian_ccmatrix_v2_best_loss_bleu_pipeline_en_5.5.0_3.0_1725766236490.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
+
+pipeline = PretrainedPipeline("opus_maltese_english_indonesian_ccmatrix_v2_best_loss_bleu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_indonesian_ccmatrix_v2_best_loss_bleu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_indonesian_ccmatrix_v2_best_loss_bleu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|482.4 MB|
+
+## References
+
+https://huggingface.co/yonathanstwn/opus-mt-en-id-ccmatrix-v2-best-loss-bleu
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_italian_finetuned_50000_english_tonga_tonga_islands_italian_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_italian_finetuned_50000_english_tonga_tonga_islands_italian_en.md
new file mode 100644
index 00000000000000..2f3ac2a248fa23
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_italian_finetuned_50000_english_tonga_tonga_islands_italian_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_italian_finetuned_50000_english_tonga_tonga_islands_italian MarianTransformer from VFiona
+author: John Snow Labs
+name: opus_maltese_english_italian_finetuned_50000_english_tonga_tonga_islands_italian
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_italian_finetuned_50000_english_tonga_tonga_islands_italian` is a English model originally trained by VFiona.
+
+{:.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/opus_maltese_english_italian_finetuned_50000_english_tonga_tonga_islands_italian_en_5.5.0_3.0_1725831546047.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_italian_finetuned_50000_english_tonga_tonga_islands_italian_en_5.5.0_3.0_1725831546047.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_italian_finetuned_50000_english_tonga_tonga_islands_italian","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_italian_finetuned_50000_english_tonga_tonga_islands_italian","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_italian_finetuned_50000_english_tonga_tonga_islands_italian|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|622.8 MB|
+
+## References
+
+https://huggingface.co/VFiona/opus-mt-en-it-finetuned_50000-en-to-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_italian_finetuned_50000_english_tonga_tonga_islands_italian_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_italian_finetuned_50000_english_tonga_tonga_islands_italian_pipeline_en.md
new file mode 100644
index 00000000000000..383d9be09e82e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_italian_finetuned_50000_english_tonga_tonga_islands_italian_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_italian_finetuned_50000_english_tonga_tonga_islands_italian_pipeline pipeline MarianTransformer from VFiona
+author: John Snow Labs
+name: opus_maltese_english_italian_finetuned_50000_english_tonga_tonga_islands_italian_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_italian_finetuned_50000_english_tonga_tonga_islands_italian_pipeline` is a English model originally trained by VFiona.
+
+{:.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/opus_maltese_english_italian_finetuned_50000_english_tonga_tonga_islands_italian_pipeline_en_5.5.0_3.0_1725831579801.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_italian_finetuned_50000_english_tonga_tonga_islands_italian_pipeline_en_5.5.0_3.0_1725831579801.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
+
+pipeline = PretrainedPipeline("opus_maltese_english_italian_finetuned_50000_english_tonga_tonga_islands_italian_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_italian_finetuned_50000_english_tonga_tonga_islands_italian_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_italian_finetuned_50000_english_tonga_tonga_islands_italian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|623.3 MB|
+
+## References
+
+https://huggingface.co/VFiona/opus-mt-en-it-finetuned_50000-en-to-it
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_aiboo_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_aiboo_en.md
new file mode 100644
index 00000000000000..b409e9060da11c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_aiboo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_aiboo MarianTransformer from aiBoo
+author: John Snow Labs
+name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_aiboo
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_aiboo` is a English model originally trained by aiBoo.
+
+{:.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/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_aiboo_en_5.5.0_3.0_1725796112027.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_aiboo_en_5.5.0_3.0_1725796112027.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_aiboo","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_aiboo","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_aiboo|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.6 MB|
+
+## References
+
+https://huggingface.co/aiBoo/opus-mt-en-ro-finetuned-en-to-ro
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_aiboo_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_aiboo_pipeline_en.md
new file mode 100644
index 00000000000000..0804c2340a96da
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_aiboo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_aiboo_pipeline pipeline MarianTransformer from aiBoo
+author: John Snow Labs
+name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_aiboo_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_aiboo_pipeline` is a English model originally trained by aiBoo.
+
+{:.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/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_aiboo_pipeline_en_5.5.0_3.0_1725796135739.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_aiboo_pipeline_en_5.5.0_3.0_1725796135739.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
+
+pipeline = PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_aiboo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_aiboo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_aiboo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|509.2 MB|
+
+## References
+
+https://huggingface.co/aiBoo/opus-mt-en-ro-finetuned-en-to-ro
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_erdody_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_erdody_en.md
new file mode 100644
index 00000000000000..587861e5d8d83c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_erdody_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_erdody MarianTransformer from erdody
+author: John Snow Labs
+name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_erdody
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_erdody` is a English model originally trained by erdody.
+
+{:.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/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_erdody_en_5.5.0_3.0_1725832560869.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_erdody_en_5.5.0_3.0_1725832560869.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_erdody","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_erdody","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_erdody|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.6 MB|
+
+## References
+
+https://huggingface.co/erdody/opus-mt-en-ro-finetuned-en-to-ro
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_erdody_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_erdody_pipeline_en.md
new file mode 100644
index 00000000000000..4477d6b553dc2e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_erdody_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_erdody_pipeline pipeline MarianTransformer from erdody
+author: John Snow Labs
+name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_erdody_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_erdody_pipeline` is a English model originally trained by erdody.
+
+{:.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/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_erdody_pipeline_en_5.5.0_3.0_1725832585650.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_erdody_pipeline_en_5.5.0_3.0_1725832585650.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
+
+pipeline = PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_erdody_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_erdody_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_erdody_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|509.2 MB|
+
+## References
+
+https://huggingface.co/erdody/opus-mt-en-ro-finetuned-en-to-ro
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_managementengineer_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_managementengineer_pipeline_en.md
new file mode 100644
index 00000000000000..cacc985dc45dfa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_managementengineer_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_managementengineer_pipeline pipeline MarianTransformer from ManagementEngineer
+author: John Snow Labs
+name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_managementengineer_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_managementengineer_pipeline` is a English model originally trained by ManagementEngineer.
+
+{:.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/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_managementengineer_pipeline_en_5.5.0_3.0_1725839871814.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_managementengineer_pipeline_en_5.5.0_3.0_1725839871814.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
+
+pipeline = PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_managementengineer_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_managementengineer_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_managementengineer_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|509.2 MB|
+
+## References
+
+https://huggingface.co/ManagementEngineer/opus-mt-en-ro-finetuned-en-to-ro
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_maryaai_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_maryaai_pipeline_en.md
new file mode 100644
index 00000000000000..d71d49db0a0ab2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_maryaai_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_maryaai_pipeline pipeline MarianTransformer from MaryaAI
+author: John Snow Labs
+name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_maryaai_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_maryaai_pipeline` is a English model originally trained by MaryaAI.
+
+{:.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/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_maryaai_pipeline_en_5.5.0_3.0_1725796226935.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_maryaai_pipeline_en_5.5.0_3.0_1725796226935.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
+
+pipeline = PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_maryaai_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_maryaai_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_maryaai_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|509.1 MB|
+
+## References
+
+https://huggingface.co/MaryaAI/opus-mt-en-ro-finetuned-en-to-ro
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_moanlb_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_moanlb_en.md
new file mode 100644
index 00000000000000..8b1d8bbb2e57ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_moanlb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_moanlb MarianTransformer from moanlb
+author: John Snow Labs
+name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_moanlb
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_moanlb` is a English model originally trained by moanlb.
+
+{:.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/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_moanlb_en_5.5.0_3.0_1725766546363.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_moanlb_en_5.5.0_3.0_1725766546363.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_moanlb","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_moanlb","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_moanlb|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.6 MB|
+
+## References
+
+https://huggingface.co/moanlb/opus-mt-en-ro-finetuned-en-to-ro
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_ncduy_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_ncduy_en.md
new file mode 100644
index 00000000000000..f4254e5b913494
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_ncduy_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_ncduy MarianTransformer from ncduy
+author: John Snow Labs
+name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_ncduy
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_ncduy` is a English model originally trained by ncduy.
+
+{:.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/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_ncduy_en_5.5.0_3.0_1725795095196.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_ncduy_en_5.5.0_3.0_1725795095196.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_ncduy","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_ncduy","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_ncduy|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.6 MB|
+
+## References
+
+https://huggingface.co/ncduy/opus-mt-en-ro-finetuned-en-to-ro
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_robbespo_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_robbespo_pipeline_en.md
new file mode 100644
index 00000000000000..2c9885e33d8ef9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_robbespo_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_robbespo_pipeline pipeline MarianTransformer from robbespo
+author: John Snow Labs
+name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_robbespo_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_robbespo_pipeline` is a English model originally trained by robbespo.
+
+{:.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/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_robbespo_pipeline_en_5.5.0_3.0_1725832489374.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_robbespo_pipeline_en_5.5.0_3.0_1725832489374.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
+
+pipeline = PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_robbespo_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_robbespo_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_robbespo_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|509.2 MB|
+
+## References
+
+https://huggingface.co/robbespo/opus-mt-en-ro-finetuned-en-to-ro
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_slimamel_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_slimamel_pipeline_en.md
new file mode 100644
index 00000000000000..e15f9d447f5ec6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_slimamel_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_slimamel_pipeline pipeline MarianTransformer from slimamel
+author: John Snow Labs
+name: opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_slimamel_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_slimamel_pipeline` is a English model originally trained by slimamel.
+
+{:.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/opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_slimamel_pipeline_en_5.5.0_3.0_1725765572955.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_slimamel_pipeline_en_5.5.0_3.0_1725765572955.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
+
+pipeline = PretrainedPipeline("opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_slimamel_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_slimamel_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_russian_finetuned_english_tonga_tonga_islands_russian_slimamel_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|526.0 MB|
+
+## References
+
+https://huggingface.co/slimamel/opus-mt-en-ru-finetuned-en-to-ru
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_pbb_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_pbb_v2_pipeline_en.md
new file mode 100644
index 00000000000000..2844240d2da6ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_pbb_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_pbb_v2_pipeline pipeline MarianTransformer from mekjr1
+author: John Snow Labs
+name: opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_pbb_v2_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_pbb_v2_pipeline` is a English model originally trained by mekjr1.
+
+{:.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/opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_pbb_v2_pipeline_en_5.5.0_3.0_1725824162451.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_pbb_v2_pipeline_en_5.5.0_3.0_1725824162451.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
+
+pipeline = PretrainedPipeline("opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_pbb_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_pbb_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_spanish_finetuned_spanish_tonga_tonga_islands_pbb_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|540.5 MB|
+
+## References
+
+https://huggingface.co/mekjr1/opus-mt-en-es-finetuned-es-to-pbb-v2
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_vietnamese_own_finetuned_english_tonga_tonga_islands_vietnamese_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_vietnamese_own_finetuned_english_tonga_tonga_islands_vietnamese_en.md
new file mode 100644
index 00000000000000..d6eae6a79a87c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_english_vietnamese_own_finetuned_english_tonga_tonga_islands_vietnamese_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_vietnamese_own_finetuned_english_tonga_tonga_islands_vietnamese MarianTransformer from ncduy
+author: John Snow Labs
+name: opus_maltese_english_vietnamese_own_finetuned_english_tonga_tonga_islands_vietnamese
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_vietnamese_own_finetuned_english_tonga_tonga_islands_vietnamese` is a English model originally trained by ncduy.
+
+{:.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/opus_maltese_english_vietnamese_own_finetuned_english_tonga_tonga_islands_vietnamese_en_5.5.0_3.0_1725765505054.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_vietnamese_own_finetuned_english_tonga_tonga_islands_vietnamese_en_5.5.0_3.0_1725765505054.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_vietnamese_own_finetuned_english_tonga_tonga_islands_vietnamese","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_vietnamese_own_finetuned_english_tonga_tonga_islands_vietnamese","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_vietnamese_own_finetuned_english_tonga_tonga_islands_vietnamese|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|476.6 MB|
+
+## References
+
+https://huggingface.co/ncduy/opus-mt-en-vi-own-finetuned-en-to-vi
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_french_yat_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_french_yat_pipeline_en.md
new file mode 100644
index 00000000000000..48b7cdaf86f6ad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_french_yat_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_french_yat_pipeline pipeline MarianTransformer from pt4c
+author: John Snow Labs
+name: opus_maltese_french_yat_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_french_yat_pipeline` is a English model originally trained by pt4c.
+
+{:.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/opus_maltese_french_yat_pipeline_en_5.5.0_3.0_1725831511296.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_french_yat_pipeline_en_5.5.0_3.0_1725831511296.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
+
+pipeline = PretrainedPipeline("opus_maltese_french_yat_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_french_yat_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_french_yat_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|507.4 MB|
+
+## References
+
+https://huggingface.co/pt4c/opus-mt-fr-yat
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_ganda_english_informal_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_ganda_english_informal_v1_pipeline_en.md
new file mode 100644
index 00000000000000..2ccca5ccf9505e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_ganda_english_informal_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_ganda_english_informal_v1_pipeline pipeline MarianTransformer from MubarakB
+author: John Snow Labs
+name: opus_maltese_ganda_english_informal_v1_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_ganda_english_informal_v1_pipeline` is a English model originally trained by MubarakB.
+
+{:.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/opus_maltese_ganda_english_informal_v1_pipeline_en_5.5.0_3.0_1725795890247.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_ganda_english_informal_v1_pipeline_en_5.5.0_3.0_1725795890247.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
+
+pipeline = PretrainedPipeline("opus_maltese_ganda_english_informal_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_ganda_english_informal_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_ganda_english_informal_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|513.7 MB|
+
+## References
+
+https://huggingface.co/MubarakB/opus-mt-lg-en-informal-v1
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_korean_english_finetuned_korean_tonga_tonga_islands_english_2780616_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_korean_english_finetuned_korean_tonga_tonga_islands_english_2780616_pipeline_en.md
new file mode 100644
index 00000000000000..2ad629892c5a87
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_korean_english_finetuned_korean_tonga_tonga_islands_english_2780616_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_korean_english_finetuned_korean_tonga_tonga_islands_english_2780616_pipeline pipeline MarianTransformer from alphahg
+author: John Snow Labs
+name: opus_maltese_korean_english_finetuned_korean_tonga_tonga_islands_english_2780616_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_korean_english_finetuned_korean_tonga_tonga_islands_english_2780616_pipeline` is a English model originally trained by alphahg.
+
+{:.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/opus_maltese_korean_english_finetuned_korean_tonga_tonga_islands_english_2780616_pipeline_en_5.5.0_3.0_1725795685122.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_korean_english_finetuned_korean_tonga_tonga_islands_english_2780616_pipeline_en_5.5.0_3.0_1725795685122.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
+
+pipeline = PretrainedPipeline("opus_maltese_korean_english_finetuned_korean_tonga_tonga_islands_english_2780616_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_korean_english_finetuned_korean_tonga_tonga_islands_english_2780616_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_korean_english_finetuned_korean_tonga_tonga_islands_english_2780616_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|541.3 MB|
+
+## References
+
+https://huggingface.co/alphahg/opus-mt-ko-en-finetuned-ko-to-en-2780616
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_romance_english_finetuned_npomo_english_5_epochs_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_romance_english_finetuned_npomo_english_5_epochs_en.md
new file mode 100644
index 00000000000000..9bb35d8d81af0e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_romance_english_finetuned_npomo_english_5_epochs_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_romance_english_finetuned_npomo_english_5_epochs MarianTransformer from UnassumingOwl
+author: John Snow Labs
+name: opus_maltese_romance_english_finetuned_npomo_english_5_epochs
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_romance_english_finetuned_npomo_english_5_epochs` is a English model originally trained by UnassumingOwl.
+
+{:.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/opus_maltese_romance_english_finetuned_npomo_english_5_epochs_en_5.5.0_3.0_1725839841506.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_romance_english_finetuned_npomo_english_5_epochs_en_5.5.0_3.0_1725839841506.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_romance_english_finetuned_npomo_english_5_epochs","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_romance_english_finetuned_npomo_english_5_epochs","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_romance_english_finetuned_npomo_english_5_epochs|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|538.9 MB|
+
+## References
+
+https://huggingface.co/UnassumingOwl/opus-mt-ROMANCE-en-finetuned-npomo-en-5-epochs
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_romance_english_finetuned_npomo_english_5_epochs_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_romance_english_finetuned_npomo_english_5_epochs_pipeline_en.md
new file mode 100644
index 00000000000000..36d01e2fbb1752
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_romance_english_finetuned_npomo_english_5_epochs_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_romance_english_finetuned_npomo_english_5_epochs_pipeline pipeline MarianTransformer from UnassumingOwl
+author: John Snow Labs
+name: opus_maltese_romance_english_finetuned_npomo_english_5_epochs_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_romance_english_finetuned_npomo_english_5_epochs_pipeline` is a English model originally trained by UnassumingOwl.
+
+{:.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/opus_maltese_romance_english_finetuned_npomo_english_5_epochs_pipeline_en_5.5.0_3.0_1725839871971.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_romance_english_finetuned_npomo_english_5_epochs_pipeline_en_5.5.0_3.0_1725839871971.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
+
+pipeline = PretrainedPipeline("opus_maltese_romance_english_finetuned_npomo_english_5_epochs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_romance_english_finetuned_npomo_english_5_epochs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_romance_english_finetuned_npomo_english_5_epochs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|539.5 MB|
+
+## References
+
+https://huggingface.co/UnassumingOwl/opus-mt-ROMANCE-en-finetuned-npomo-en-5-epochs
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_ilevs_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_ilevs_en.md
new file mode 100644
index 00000000000000..7118c0d22d1a2d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_ilevs_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_ilevs MarianTransformer from ilevs
+author: John Snow Labs
+name: opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_ilevs
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_ilevs` is a English model originally trained by ilevs.
+
+{:.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/opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_ilevs_en_5.5.0_3.0_1725832378200.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_ilevs_en_5.5.0_3.0_1725832378200.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_ilevs","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_ilevs","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_ilevs|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|526.3 MB|
+
+## References
+
+https://huggingface.co/ilevs/opus-mt-ru-en-finetuned-ru-to-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_ilevs_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_ilevs_pipeline_en.md
new file mode 100644
index 00000000000000..8822ab93e3bf7f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_ilevs_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_ilevs_pipeline pipeline MarianTransformer from ilevs
+author: John Snow Labs
+name: opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_ilevs_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_ilevs_pipeline` is a English model originally trained by ilevs.
+
+{:.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/opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_ilevs_pipeline_en_5.5.0_3.0_1725832406299.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_ilevs_pipeline_en_5.5.0_3.0_1725832406299.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
+
+pipeline = PretrainedPipeline("opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_ilevs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_ilevs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_ilevs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|526.8 MB|
+
+## References
+
+https://huggingface.co/ilevs/opus-mt-ru-en-finetuned-ru-to-en
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_russian_ukrainian_finetuned_russian_tonga_tonga_islands_ukrainian_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_russian_ukrainian_finetuned_russian_tonga_tonga_islands_ukrainian_en.md
new file mode 100644
index 00000000000000..8beaa83a37ad52
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_russian_ukrainian_finetuned_russian_tonga_tonga_islands_ukrainian_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_russian_ukrainian_finetuned_russian_tonga_tonga_islands_ukrainian MarianTransformer from x51xxx
+author: John Snow Labs
+name: opus_maltese_russian_ukrainian_finetuned_russian_tonga_tonga_islands_ukrainian
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_russian_ukrainian_finetuned_russian_tonga_tonga_islands_ukrainian` is a English model originally trained by x51xxx.
+
+{:.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/opus_maltese_russian_ukrainian_finetuned_russian_tonga_tonga_islands_ukrainian_en_5.5.0_3.0_1725765868860.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_russian_ukrainian_finetuned_russian_tonga_tonga_islands_ukrainian_en_5.5.0_3.0_1725765868860.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_russian_ukrainian_finetuned_russian_tonga_tonga_islands_ukrainian","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_russian_ukrainian_finetuned_russian_tonga_tonga_islands_ukrainian","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_russian_ukrainian_finetuned_russian_tonga_tonga_islands_ukrainian|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|500.2 MB|
+
+## References
+
+https://huggingface.co/x51xxx/opus-mt-ru-uk-finetuned-ru-to-uk
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_russian_ukrainian_finetuned_russian_tonga_tonga_islands_ukrainian_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_russian_ukrainian_finetuned_russian_tonga_tonga_islands_ukrainian_pipeline_en.md
new file mode 100644
index 00000000000000..a4e154232d4f8d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_russian_ukrainian_finetuned_russian_tonga_tonga_islands_ukrainian_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_russian_ukrainian_finetuned_russian_tonga_tonga_islands_ukrainian_pipeline pipeline MarianTransformer from x51xxx
+author: John Snow Labs
+name: opus_maltese_russian_ukrainian_finetuned_russian_tonga_tonga_islands_ukrainian_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_russian_ukrainian_finetuned_russian_tonga_tonga_islands_ukrainian_pipeline` is a English model originally trained by x51xxx.
+
+{:.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/opus_maltese_russian_ukrainian_finetuned_russian_tonga_tonga_islands_ukrainian_pipeline_en_5.5.0_3.0_1725765892528.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_russian_ukrainian_finetuned_russian_tonga_tonga_islands_ukrainian_pipeline_en_5.5.0_3.0_1725765892528.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
+
+pipeline = PretrainedPipeline("opus_maltese_russian_ukrainian_finetuned_russian_tonga_tonga_islands_ukrainian_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_russian_ukrainian_finetuned_russian_tonga_tonga_islands_ukrainian_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_russian_ukrainian_finetuned_russian_tonga_tonga_islands_ukrainian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|500.8 MB|
+
+## References
+
+https://huggingface.co/x51xxx/opus-mt-ru-uk-finetuned-ru-to-uk
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_southern_sotho_english_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_southern_sotho_english_en.md
new file mode 100644
index 00000000000000..76eb0c6439a241
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_southern_sotho_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_southern_sotho_english MarianTransformer from cw1521
+author: John Snow Labs
+name: opus_maltese_southern_sotho_english
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_southern_sotho_english` is a English model originally trained by cw1521.
+
+{:.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/opus_maltese_southern_sotho_english_en_5.5.0_3.0_1725795332065.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_southern_sotho_english_en_5.5.0_3.0_1725795332065.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_southern_sotho_english","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_southern_sotho_english","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_southern_sotho_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.4 MB|
+
+## References
+
+https://huggingface.co/cw1521/opus-mt-st-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_spanish_english_finetuned_english_tonga_tonga_islands_spanish_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_spanish_english_finetuned_english_tonga_tonga_islands_spanish_pipeline_en.md
new file mode 100644
index 00000000000000..09ff13f16062f3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_spanish_english_finetuned_english_tonga_tonga_islands_spanish_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_spanish_english_finetuned_english_tonga_tonga_islands_spanish_pipeline pipeline MarianTransformer from hongjing0312
+author: John Snow Labs
+name: opus_maltese_spanish_english_finetuned_english_tonga_tonga_islands_spanish_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_spanish_english_finetuned_english_tonga_tonga_islands_spanish_pipeline` is a English model originally trained by hongjing0312.
+
+{:.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/opus_maltese_spanish_english_finetuned_english_tonga_tonga_islands_spanish_pipeline_en_5.5.0_3.0_1725839912384.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_spanish_english_finetuned_english_tonga_tonga_islands_spanish_pipeline_en_5.5.0_3.0_1725839912384.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
+
+pipeline = PretrainedPipeline("opus_maltese_spanish_english_finetuned_english_tonga_tonga_islands_spanish_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_spanish_english_finetuned_english_tonga_tonga_islands_spanish_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_spanish_english_finetuned_english_tonga_tonga_islands_spanish_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|539.4 MB|
+
+## References
+
+https://huggingface.co/hongjing0312/opus-mt-es-en-finetuned-en-to-es
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_tigrinya_english_finetuned_npomo_english_5_epochs_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_tigrinya_english_finetuned_npomo_english_5_epochs_en.md
new file mode 100644
index 00000000000000..0aa76455fd17e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_tigrinya_english_finetuned_npomo_english_5_epochs_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_tigrinya_english_finetuned_npomo_english_5_epochs MarianTransformer from UnassumingOwl
+author: John Snow Labs
+name: opus_maltese_tigrinya_english_finetuned_npomo_english_5_epochs
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_tigrinya_english_finetuned_npomo_english_5_epochs` is a English model originally trained by UnassumingOwl.
+
+{:.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/opus_maltese_tigrinya_english_finetuned_npomo_english_5_epochs_en_5.5.0_3.0_1725832307507.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_tigrinya_english_finetuned_npomo_english_5_epochs_en_5.5.0_3.0_1725832307507.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_tigrinya_english_finetuned_npomo_english_5_epochs","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_tigrinya_english_finetuned_npomo_english_5_epochs","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_tigrinya_english_finetuned_npomo_english_5_epochs|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|528.6 MB|
+
+## References
+
+https://huggingface.co/UnassumingOwl/opus-mt-ti-en-finetuned-npomo-en-5-epochs
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_tigrinya_english_finetuned_npomo_english_5_epochs_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_tigrinya_english_finetuned_npomo_english_5_epochs_pipeline_en.md
new file mode 100644
index 00000000000000..35b7db580e20c6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_tigrinya_english_finetuned_npomo_english_5_epochs_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_tigrinya_english_finetuned_npomo_english_5_epochs_pipeline pipeline MarianTransformer from UnassumingOwl
+author: John Snow Labs
+name: opus_maltese_tigrinya_english_finetuned_npomo_english_5_epochs_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_tigrinya_english_finetuned_npomo_english_5_epochs_pipeline` is a English model originally trained by UnassumingOwl.
+
+{:.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/opus_maltese_tigrinya_english_finetuned_npomo_english_5_epochs_pipeline_en_5.5.0_3.0_1725832334460.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_tigrinya_english_finetuned_npomo_english_5_epochs_pipeline_en_5.5.0_3.0_1725832334460.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
+
+pipeline = PretrainedPipeline("opus_maltese_tigrinya_english_finetuned_npomo_english_5_epochs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_tigrinya_english_finetuned_npomo_english_5_epochs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_tigrinya_english_finetuned_npomo_english_5_epochs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|529.1 MB|
+
+## References
+
+https://huggingface.co/UnassumingOwl/opus-mt-ti-en-finetuned-npomo-en-5-epochs
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_turkish_english_finetuned_npomo_english_5_epochs_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_turkish_english_finetuned_npomo_english_5_epochs_pipeline_en.md
new file mode 100644
index 00000000000000..07a7889c8456cd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-opus_maltese_turkish_english_finetuned_npomo_english_5_epochs_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_turkish_english_finetuned_npomo_english_5_epochs_pipeline pipeline MarianTransformer from UnassumingOwl
+author: John Snow Labs
+name: opus_maltese_turkish_english_finetuned_npomo_english_5_epochs_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_turkish_english_finetuned_npomo_english_5_epochs_pipeline` is a English model originally trained by UnassumingOwl.
+
+{:.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/opus_maltese_turkish_english_finetuned_npomo_english_5_epochs_pipeline_en_5.5.0_3.0_1725831835606.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_turkish_english_finetuned_npomo_english_5_epochs_pipeline_en_5.5.0_3.0_1725831835606.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
+
+pipeline = PretrainedPipeline("opus_maltese_turkish_english_finetuned_npomo_english_5_epochs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_turkish_english_finetuned_npomo_english_5_epochs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_turkish_english_finetuned_npomo_english_5_epochs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|525.7 MB|
+
+## References
+
+https://huggingface.co/UnassumingOwl/opus-mt-tr-en-finetuned-npomo-en-5-epochs
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-output_lobrien001_en.md b/docs/_posts/ahmedlone127/2024-09-08-output_lobrien001_en.md
new file mode 100644
index 00000000000000..9dc57a5688119e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-output_lobrien001_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English output_lobrien001 DistilBertForTokenClassification from lobrien001
+author: John Snow Labs
+name: output_lobrien001
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`output_lobrien001` is a English model originally trained by lobrien001.
+
+{:.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/output_lobrien001_en_5.5.0_3.0_1725788942533.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/output_lobrien001_en_5.5.0_3.0_1725788942533.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("output_lobrien001","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("output_lobrien001", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|output_lobrien001|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/lobrien001/output
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-output_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-output_pipeline_en.md
new file mode 100644
index 00000000000000..6bae961da078db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-output_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English output_pipeline pipeline MarianTransformer from bazaluk
+author: John Snow Labs
+name: output_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`output_pipeline` is a English model originally trained by bazaluk.
+
+{:.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/output_pipeline_en_5.5.0_3.0_1725766585208.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/output_pipeline_en_5.5.0_3.0_1725766585208.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
+
+pipeline = PretrainedPipeline("output_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("output_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|output_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|508.9 MB|
+
+## References
+
+https://huggingface.co/bazaluk/output
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-paraphrase_mpnet_base_v2_french_english_en.md b/docs/_posts/ahmedlone127/2024-09-08-paraphrase_mpnet_base_v2_french_english_en.md
new file mode 100644
index 00000000000000..b943099b984b36
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-paraphrase_mpnet_base_v2_french_english_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English paraphrase_mpnet_base_v2_french_english MPNetEmbeddings from RobinMeneust
+author: John Snow Labs
+name: paraphrase_mpnet_base_v2_french_english
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`paraphrase_mpnet_base_v2_french_english` is a English model originally trained by RobinMeneust.
+
+{:.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/paraphrase_mpnet_base_v2_french_english_en_5.5.0_3.0_1725816717162.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/paraphrase_mpnet_base_v2_french_english_en_5.5.0_3.0_1725816717162.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("paraphrase_mpnet_base_v2_french_english","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("paraphrase_mpnet_base_v2_french_english","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|paraphrase_mpnet_base_v2_french_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/RobinMeneust/paraphrase-mpnet-base-v2-fr-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-paraphrase_mpnet_base_v2_french_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-paraphrase_mpnet_base_v2_french_english_pipeline_en.md
new file mode 100644
index 00000000000000..a5715170fdf95b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-paraphrase_mpnet_base_v2_french_english_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English paraphrase_mpnet_base_v2_french_english_pipeline pipeline MPNetEmbeddings from RobinMeneust
+author: John Snow Labs
+name: paraphrase_mpnet_base_v2_french_english_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`paraphrase_mpnet_base_v2_french_english_pipeline` is a English model originally trained by RobinMeneust.
+
+{:.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/paraphrase_mpnet_base_v2_french_english_pipeline_en_5.5.0_3.0_1725816749778.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/paraphrase_mpnet_base_v2_french_english_pipeline_en_5.5.0_3.0_1725816749778.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
+
+pipeline = PretrainedPipeline("paraphrase_mpnet_base_v2_french_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("paraphrase_mpnet_base_v2_french_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|paraphrase_mpnet_base_v2_french_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/RobinMeneust/paraphrase-mpnet-base-v2-fr-en
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-paraphrase_mpnet_base_v2_setfit_emotions_en.md b/docs/_posts/ahmedlone127/2024-09-08-paraphrase_mpnet_base_v2_setfit_emotions_en.md
new file mode 100644
index 00000000000000..c1fd92707cf5de
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-paraphrase_mpnet_base_v2_setfit_emotions_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English paraphrase_mpnet_base_v2_setfit_emotions MPNetEmbeddings from moshew
+author: John Snow Labs
+name: paraphrase_mpnet_base_v2_setfit_emotions
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`paraphrase_mpnet_base_v2_setfit_emotions` is a English model originally trained by moshew.
+
+{:.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/paraphrase_mpnet_base_v2_setfit_emotions_en_5.5.0_3.0_1725816224243.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/paraphrase_mpnet_base_v2_setfit_emotions_en_5.5.0_3.0_1725816224243.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("paraphrase_mpnet_base_v2_setfit_emotions","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("paraphrase_mpnet_base_v2_setfit_emotions","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|paraphrase_mpnet_base_v2_setfit_emotions|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/moshew/paraphrase-mpnet-base-v2_SetFit_emotions
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-parsbert_nli_farstail_farsick_en.md b/docs/_posts/ahmedlone127/2024-09-08-parsbert_nli_farstail_farsick_en.md
new file mode 100644
index 00000000000000..8c50a85d9ecb75
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-parsbert_nli_farstail_farsick_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English parsbert_nli_farstail_farsick BertForSequenceClassification from parsi-ai-nlpclass
+author: John Snow Labs
+name: parsbert_nli_farstail_farsick
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`parsbert_nli_farstail_farsick` is a English model originally trained by parsi-ai-nlpclass.
+
+{:.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/parsbert_nli_farstail_farsick_en_5.5.0_3.0_1725839513980.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/parsbert_nli_farstail_farsick_en_5.5.0_3.0_1725839513980.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("parsbert_nli_farstail_farsick","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("parsbert_nli_farstail_farsick", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|parsbert_nli_farstail_farsick|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|443.8 MB|
+
+## References
+
+https://huggingface.co/parsi-ai-nlpclass/ParsBERT-nli-FarsTail-FarSick
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-parsbert_nli_farstail_farsick_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-parsbert_nli_farstail_farsick_pipeline_en.md
new file mode 100644
index 00000000000000..ba91a56f0719b6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-parsbert_nli_farstail_farsick_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English parsbert_nli_farstail_farsick_pipeline pipeline BertForSequenceClassification from parsi-ai-nlpclass
+author: John Snow Labs
+name: parsbert_nli_farstail_farsick_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`parsbert_nli_farstail_farsick_pipeline` is a English model originally trained by parsi-ai-nlpclass.
+
+{:.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/parsbert_nli_farstail_farsick_pipeline_en_5.5.0_3.0_1725839535101.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/parsbert_nli_farstail_farsick_pipeline_en_5.5.0_3.0_1725839535101.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
+
+pipeline = PretrainedPipeline("parsbert_nli_farstail_farsick_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("parsbert_nli_farstail_farsick_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|parsbert_nli_farstail_farsick_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|443.8 MB|
+
+## References
+
+https://huggingface.co/parsi-ai-nlpclass/ParsBERT-nli-FarsTail-FarSick
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-passage_ranker_v1_l_english_en.md b/docs/_posts/ahmedlone127/2024-09-08-passage_ranker_v1_l_english_en.md
new file mode 100644
index 00000000000000..cddc106cd93e01
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-passage_ranker_v1_l_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English passage_ranker_v1_l_english BertForSequenceClassification from sinequa
+author: John Snow Labs
+name: passage_ranker_v1_l_english
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`passage_ranker_v1_l_english` is a English model originally trained by sinequa.
+
+{:.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/passage_ranker_v1_l_english_en_5.5.0_3.0_1725768168331.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/passage_ranker_v1_l_english_en_5.5.0_3.0_1725768168331.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("passage_ranker_v1_l_english","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("passage_ranker_v1_l_english", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|passage_ranker_v1_l_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/sinequa/passage-ranker-v1-L-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-passage_ranker_v1_l_multilingual_xx.md b/docs/_posts/ahmedlone127/2024-09-08-passage_ranker_v1_l_multilingual_xx.md
new file mode 100644
index 00000000000000..9b51348a37661f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-passage_ranker_v1_l_multilingual_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual passage_ranker_v1_l_multilingual BertForSequenceClassification from sinequa
+author: John Snow Labs
+name: passage_ranker_v1_l_multilingual
+date: 2024-09-08
+tags: [xx, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`passage_ranker_v1_l_multilingual` is a Multilingual model originally trained by sinequa.
+
+{:.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/passage_ranker_v1_l_multilingual_xx_5.5.0_3.0_1725801599653.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/passage_ranker_v1_l_multilingual_xx_5.5.0_3.0_1725801599653.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("passage_ranker_v1_l_multilingual","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("passage_ranker_v1_l_multilingual", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|passage_ranker_v1_l_multilingual|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|xx|
+|Size:|466.6 MB|
+
+## References
+
+https://huggingface.co/sinequa/passage-ranker-v1-L-multilingual
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-paste_your_model_indonesian_here_en.md b/docs/_posts/ahmedlone127/2024-09-08-paste_your_model_indonesian_here_en.md
new file mode 100644
index 00000000000000..d7962ba837903e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-paste_your_model_indonesian_here_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English paste_your_model_indonesian_here DistilBertForTokenClassification from blub007
+author: John Snow Labs
+name: paste_your_model_indonesian_here
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`paste_your_model_indonesian_here` is a English model originally trained by blub007.
+
+{:.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/paste_your_model_indonesian_here_en_5.5.0_3.0_1725788516863.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/paste_your_model_indonesian_here_en_5.5.0_3.0_1725788516863.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("paste_your_model_indonesian_here","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("paste_your_model_indonesian_here", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|paste_your_model_indonesian_here|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/blub007/paste_your_model_id_here
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-portuguese_finegrained_zero_shot_en.md b/docs/_posts/ahmedlone127/2024-09-08-portuguese_finegrained_zero_shot_en.md
new file mode 100644
index 00000000000000..762be93d8a4bbd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-portuguese_finegrained_zero_shot_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English portuguese_finegrained_zero_shot XlmRoBertaForSequenceClassification from edwardgowsmith
+author: John Snow Labs
+name: portuguese_finegrained_zero_shot
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`portuguese_finegrained_zero_shot` is a English model originally trained by edwardgowsmith.
+
+{:.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/portuguese_finegrained_zero_shot_en_5.5.0_3.0_1725799792929.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/portuguese_finegrained_zero_shot_en_5.5.0_3.0_1725799792929.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("portuguese_finegrained_zero_shot","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("portuguese_finegrained_zero_shot", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|portuguese_finegrained_zero_shot|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|782.5 MB|
+
+## References
+
+https://huggingface.co/edwardgowsmith/pt-finegrained-zero-shot
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-portuguese_finegrained_zero_shot_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-portuguese_finegrained_zero_shot_pipeline_en.md
new file mode 100644
index 00000000000000..59f74f8dbf3d91
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-portuguese_finegrained_zero_shot_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English portuguese_finegrained_zero_shot_pipeline pipeline XlmRoBertaForSequenceClassification from edwardgowsmith
+author: John Snow Labs
+name: portuguese_finegrained_zero_shot_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`portuguese_finegrained_zero_shot_pipeline` is a English model originally trained by edwardgowsmith.
+
+{:.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/portuguese_finegrained_zero_shot_pipeline_en_5.5.0_3.0_1725799929904.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/portuguese_finegrained_zero_shot_pipeline_en_5.5.0_3.0_1725799929904.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
+
+pipeline = PretrainedPipeline("portuguese_finegrained_zero_shot_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("portuguese_finegrained_zero_shot_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|portuguese_finegrained_zero_shot_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|782.5 MB|
+
+## References
+
+https://huggingface.co/edwardgowsmith/pt-finegrained-zero-shot
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-portuguese_up_xlmr_falsetrue_0_0_best_en.md b/docs/_posts/ahmedlone127/2024-09-08-portuguese_up_xlmr_falsetrue_0_0_best_en.md
new file mode 100644
index 00000000000000..849d269bade5ec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-portuguese_up_xlmr_falsetrue_0_0_best_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English portuguese_up_xlmr_falsetrue_0_0_best XlmRoBertaForSequenceClassification from harish
+author: John Snow Labs
+name: portuguese_up_xlmr_falsetrue_0_0_best
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`portuguese_up_xlmr_falsetrue_0_0_best` is a English model originally trained by harish.
+
+{:.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/portuguese_up_xlmr_falsetrue_0_0_best_en_5.5.0_3.0_1725800402520.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/portuguese_up_xlmr_falsetrue_0_0_best_en_5.5.0_3.0_1725800402520.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("portuguese_up_xlmr_falsetrue_0_0_best","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("portuguese_up_xlmr_falsetrue_0_0_best", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|portuguese_up_xlmr_falsetrue_0_0_best|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|782.4 MB|
+
+## References
+
+https://huggingface.co/harish/PT-UP-xlmR-FalseTrue-0_0_BEST
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-portuguese_up_xlmr_falsetrue_0_0_best_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-portuguese_up_xlmr_falsetrue_0_0_best_pipeline_en.md
new file mode 100644
index 00000000000000..bd5f7166b2d9d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-portuguese_up_xlmr_falsetrue_0_0_best_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English portuguese_up_xlmr_falsetrue_0_0_best_pipeline pipeline XlmRoBertaForSequenceClassification from harish
+author: John Snow Labs
+name: portuguese_up_xlmr_falsetrue_0_0_best_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`portuguese_up_xlmr_falsetrue_0_0_best_pipeline` is a English model originally trained by harish.
+
+{:.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/portuguese_up_xlmr_falsetrue_0_0_best_pipeline_en_5.5.0_3.0_1725800537327.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/portuguese_up_xlmr_falsetrue_0_0_best_pipeline_en_5.5.0_3.0_1725800537327.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
+
+pipeline = PretrainedPipeline("portuguese_up_xlmr_falsetrue_0_0_best_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("portuguese_up_xlmr_falsetrue_0_0_best_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|portuguese_up_xlmr_falsetrue_0_0_best_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|782.4 MB|
+
+## References
+
+https://huggingface.co/harish/PT-UP-xlmR-FalseTrue-0_0_BEST
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-position_names_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-position_names_pipeline_en.md
new file mode 100644
index 00000000000000..1027df323d3a92
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-position_names_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English position_names_pipeline pipeline DistilBertForTokenClassification from chris1tava
+author: John Snow Labs
+name: position_names_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`position_names_pipeline` is a English model originally trained by chris1tava.
+
+{:.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/position_names_pipeline_en_5.5.0_3.0_1725827644157.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/position_names_pipeline_en_5.5.0_3.0_1725827644157.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
+
+pipeline = PretrainedPipeline("position_names_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("position_names_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|position_names_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/chris1tava/position_names
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-positive_news_snippet_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-positive_news_snippet_model_pipeline_en.md
new file mode 100644
index 00000000000000..dd20f546ddde65
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-positive_news_snippet_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English positive_news_snippet_model_pipeline pipeline DistilBertForSequenceClassification from ripjar
+author: John Snow Labs
+name: positive_news_snippet_model_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`positive_news_snippet_model_pipeline` is a English model originally trained by ripjar.
+
+{:.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/positive_news_snippet_model_pipeline_en_5.5.0_3.0_1725808737018.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/positive_news_snippet_model_pipeline_en_5.5.0_3.0_1725808737018.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
+
+pipeline = PretrainedPipeline("positive_news_snippet_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("positive_news_snippet_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|positive_news_snippet_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ripjar/positive_news_snippet_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-predict_perception_xlmr_blame_none_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-predict_perception_xlmr_blame_none_pipeline_en.md
new file mode 100644
index 00000000000000..37c6235538d29f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-predict_perception_xlmr_blame_none_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English predict_perception_xlmr_blame_none_pipeline pipeline XlmRoBertaForSequenceClassification from responsibility-framing
+author: John Snow Labs
+name: predict_perception_xlmr_blame_none_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`predict_perception_xlmr_blame_none_pipeline` is a English model originally trained by responsibility-framing.
+
+{:.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/predict_perception_xlmr_blame_none_pipeline_en_5.5.0_3.0_1725799955801.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/predict_perception_xlmr_blame_none_pipeline_en_5.5.0_3.0_1725799955801.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
+
+pipeline = PretrainedPipeline("predict_perception_xlmr_blame_none_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("predict_perception_xlmr_blame_none_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|predict_perception_xlmr_blame_none_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|837.6 MB|
+
+## References
+
+https://huggingface.co/responsibility-framing/predict-perception-xlmr-blame-none
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-predict_perception_xlmr_focus_assassin_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-predict_perception_xlmr_focus_assassin_pipeline_en.md
new file mode 100644
index 00000000000000..92bca48051bf81
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-predict_perception_xlmr_focus_assassin_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English predict_perception_xlmr_focus_assassin_pipeline pipeline XlmRoBertaForSequenceClassification from responsibility-framing
+author: John Snow Labs
+name: predict_perception_xlmr_focus_assassin_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`predict_perception_xlmr_focus_assassin_pipeline` is a English model originally trained by responsibility-framing.
+
+{:.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/predict_perception_xlmr_focus_assassin_pipeline_en_5.5.0_3.0_1725780945600.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/predict_perception_xlmr_focus_assassin_pipeline_en_5.5.0_3.0_1725780945600.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
+
+pipeline = PretrainedPipeline("predict_perception_xlmr_focus_assassin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("predict_perception_xlmr_focus_assassin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|predict_perception_xlmr_focus_assassin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|837.6 MB|
+
+## References
+
+https://huggingface.co/responsibility-framing/predict-perception-xlmr-focus-assassin
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-prediksi_emosi_indobert_id.md b/docs/_posts/ahmedlone127/2024-09-08-prediksi_emosi_indobert_id.md
new file mode 100644
index 00000000000000..f423543377ccd1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-prediksi_emosi_indobert_id.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Indonesian prediksi_emosi_indobert BertForSequenceClassification from azizp128
+author: John Snow Labs
+name: prediksi_emosi_indobert
+date: 2024-09-08
+tags: [id, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: id
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`prediksi_emosi_indobert` is a Indonesian model originally trained by azizp128.
+
+{:.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/prediksi_emosi_indobert_id_5.5.0_3.0_1725825866141.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/prediksi_emosi_indobert_id_5.5.0_3.0_1725825866141.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("prediksi_emosi_indobert","id") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("prediksi_emosi_indobert", "id")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|prediksi_emosi_indobert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|id|
+|Size:|466.4 MB|
+
+## References
+
+https://huggingface.co/azizp128/prediksi-emosi-indobert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-prediksi_emosi_indobert_pipeline_id.md b/docs/_posts/ahmedlone127/2024-09-08-prediksi_emosi_indobert_pipeline_id.md
new file mode 100644
index 00000000000000..aa1f51f62a60e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-prediksi_emosi_indobert_pipeline_id.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Indonesian prediksi_emosi_indobert_pipeline pipeline BertForSequenceClassification from azizp128
+author: John Snow Labs
+name: prediksi_emosi_indobert_pipeline
+date: 2024-09-08
+tags: [id, open_source, pipeline, onnx]
+task: Text Classification
+language: id
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`prediksi_emosi_indobert_pipeline` is a Indonesian model originally trained by azizp128.
+
+{:.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/prediksi_emosi_indobert_pipeline_id_5.5.0_3.0_1725825888549.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/prediksi_emosi_indobert_pipeline_id_5.5.0_3.0_1725825888549.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
+
+pipeline = PretrainedPipeline("prediksi_emosi_indobert_pipeline", lang = "id")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("prediksi_emosi_indobert_pipeline", lang = "id")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|prediksi_emosi_indobert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|id|
+|Size:|466.4 MB|
+
+## References
+
+https://huggingface.co/azizp128/prediksi-emosi-indobert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-psais_all_mpnet_base_v2_50shot_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-psais_all_mpnet_base_v2_50shot_pipeline_en.md
new file mode 100644
index 00000000000000..a8dafc33a51cd7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-psais_all_mpnet_base_v2_50shot_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English psais_all_mpnet_base_v2_50shot_pipeline pipeline MPNetEmbeddings from hroth01
+author: John Snow Labs
+name: psais_all_mpnet_base_v2_50shot_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`psais_all_mpnet_base_v2_50shot_pipeline` is a English model originally trained by hroth01.
+
+{:.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/psais_all_mpnet_base_v2_50shot_pipeline_en_5.5.0_3.0_1725816892267.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/psais_all_mpnet_base_v2_50shot_pipeline_en_5.5.0_3.0_1725816892267.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
+
+pipeline = PretrainedPipeline("psais_all_mpnet_base_v2_50shot_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("psais_all_mpnet_base_v2_50shot_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|psais_all_mpnet_base_v2_50shot_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/hroth01/psais-all-mpnet-base-v2-50shot
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-q2d_ep3_35_en.md b/docs/_posts/ahmedlone127/2024-09-08-q2d_ep3_35_en.md
new file mode 100644
index 00000000000000..ba88932a310f85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-q2d_ep3_35_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English q2d_ep3_35 MPNetEmbeddings from ingeol
+author: John Snow Labs
+name: q2d_ep3_35
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`q2d_ep3_35` is a English model originally trained by ingeol.
+
+{:.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/q2d_ep3_35_en_5.5.0_3.0_1725769051122.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/q2d_ep3_35_en_5.5.0_3.0_1725769051122.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("q2d_ep3_35","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("q2d_ep3_35","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|q2d_ep3_35|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/ingeol/q2d_ep3_35
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-q2d_gpt_1234_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-q2d_gpt_1234_pipeline_en.md
new file mode 100644
index 00000000000000..527600ad054e31
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-q2d_gpt_1234_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English q2d_gpt_1234_pipeline pipeline MPNetEmbeddings from ingeol
+author: John Snow Labs
+name: q2d_gpt_1234_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`q2d_gpt_1234_pipeline` is a English model originally trained by ingeol.
+
+{:.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/q2d_gpt_1234_pipeline_en_5.5.0_3.0_1725816023680.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/q2d_gpt_1234_pipeline_en_5.5.0_3.0_1725816023680.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
+
+pipeline = PretrainedPipeline("q2d_gpt_1234_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("q2d_gpt_1234_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|q2d_gpt_1234_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/ingeol/q2d_gpt_1234
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-q2e_ep3_1234_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-q2e_ep3_1234_pipeline_en.md
new file mode 100644
index 00000000000000..4f55071fba4c29
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-q2e_ep3_1234_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English q2e_ep3_1234_pipeline pipeline MPNetEmbeddings from ingeol
+author: John Snow Labs
+name: q2e_ep3_1234_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`q2e_ep3_1234_pipeline` is a English model originally trained by ingeol.
+
+{:.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/q2e_ep3_1234_pipeline_en_5.5.0_3.0_1725769228446.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/q2e_ep3_1234_pipeline_en_5.5.0_3.0_1725769228446.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
+
+pipeline = PretrainedPipeline("q2e_ep3_1234_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("q2e_ep3_1234_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|q2e_ep3_1234_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/ingeol/q2e_ep3_1234
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-q_only_ep3_1122_en.md b/docs/_posts/ahmedlone127/2024-09-08-q_only_ep3_1122_en.md
new file mode 100644
index 00000000000000..2baaeebf084047
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-q_only_ep3_1122_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English q_only_ep3_1122 MPNetEmbeddings from ingeol
+author: John Snow Labs
+name: q_only_ep3_1122
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`q_only_ep3_1122` is a English model originally trained by ingeol.
+
+{:.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/q_only_ep3_1122_en_5.5.0_3.0_1725769922098.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/q_only_ep3_1122_en_5.5.0_3.0_1725769922098.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("q_only_ep3_1122","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("q_only_ep3_1122","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|q_only_ep3_1122|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/ingeol/q_only_ep3_1122
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-q_only_ep3_1122_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-q_only_ep3_1122_pipeline_en.md
new file mode 100644
index 00000000000000..709f7cdc8a07fa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-q_only_ep3_1122_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English q_only_ep3_1122_pipeline pipeline MPNetEmbeddings from ingeol
+author: John Snow Labs
+name: q_only_ep3_1122_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`q_only_ep3_1122_pipeline` is a English model originally trained by ingeol.
+
+{:.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/q_only_ep3_1122_pipeline_en_5.5.0_3.0_1725769940253.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/q_only_ep3_1122_pipeline_en_5.5.0_3.0_1725769940253.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
+
+pipeline = PretrainedPipeline("q_only_ep3_1122_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("q_only_ep3_1122_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|q_only_ep3_1122_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/ingeol/q_only_ep3_1122
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-qa_en.md b/docs/_posts/ahmedlone127/2024-09-08-qa_en.md
new file mode 100644
index 00000000000000..f216c55b5a7e06
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-qa_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English qa DistilBertForQuestionAnswering from Ateeb
+author: John Snow Labs
+name: qa
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa` is a English model originally trained by Ateeb.
+
+{:.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/qa_en_5.5.0_3.0_1725818625464.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_en_5.5.0_3.0_1725818625464.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("qa","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("qa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Ateeb/QA
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-qa_model2_zhaoxinwind_en.md b/docs/_posts/ahmedlone127/2024-09-08-qa_model2_zhaoxinwind_en.md
new file mode 100644
index 00000000000000..6f23edf1942125
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-qa_model2_zhaoxinwind_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English qa_model2_zhaoxinwind DistilBertForQuestionAnswering from zhaoxinwind
+author: John Snow Labs
+name: qa_model2_zhaoxinwind
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_model2_zhaoxinwind` is a English model originally trained by zhaoxinwind.
+
+{:.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/qa_model2_zhaoxinwind_en_5.5.0_3.0_1725818131820.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_model2_zhaoxinwind_en_5.5.0_3.0_1725818131820.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("qa_model2_zhaoxinwind","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("qa_model2_zhaoxinwind", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_model2_zhaoxinwind|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/zhaoxinwind/QA_model2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-qa_model2_zhaoxinwind_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-qa_model2_zhaoxinwind_pipeline_en.md
new file mode 100644
index 00000000000000..db4984efaf754f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-qa_model2_zhaoxinwind_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qa_model2_zhaoxinwind_pipeline pipeline DistilBertForQuestionAnswering from zhaoxinwind
+author: John Snow Labs
+name: qa_model2_zhaoxinwind_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_model2_zhaoxinwind_pipeline` is a English model originally trained by zhaoxinwind.
+
+{:.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/qa_model2_zhaoxinwind_pipeline_en_5.5.0_3.0_1725818144873.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_model2_zhaoxinwind_pipeline_en_5.5.0_3.0_1725818144873.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
+
+pipeline = PretrainedPipeline("qa_model2_zhaoxinwind_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qa_model2_zhaoxinwind_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_model2_zhaoxinwind_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/zhaoxinwind/QA_model2
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-qa_model9_test_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-qa_model9_test_pipeline_en.md
new file mode 100644
index 00000000000000..9dd2e05397a2be
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-qa_model9_test_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qa_model9_test_pipeline pipeline RoBertaForQuestionAnswering from MattNandavong
+author: John Snow Labs
+name: qa_model9_test_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_model9_test_pipeline` is a English model originally trained by MattNandavong.
+
+{:.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/qa_model9_test_pipeline_en_5.5.0_3.0_1725757706457.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_model9_test_pipeline_en_5.5.0_3.0_1725757706457.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
+
+pipeline = PretrainedPipeline("qa_model9_test_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qa_model9_test_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_model9_test_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.6 MB|
+
+## References
+
+https://huggingface.co/MattNandavong/QA_model9-test
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-qa_model_vasanth_en.md b/docs/_posts/ahmedlone127/2024-09-08-qa_model_vasanth_en.md
new file mode 100644
index 00000000000000..756c8c3b9a0be6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-qa_model_vasanth_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English qa_model_vasanth DistilBertForQuestionAnswering from Vasanth
+author: John Snow Labs
+name: qa_model_vasanth
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_model_vasanth` is a English model originally trained by Vasanth.
+
+{:.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/qa_model_vasanth_en_5.5.0_3.0_1725823647192.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_model_vasanth_en_5.5.0_3.0_1725823647192.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("qa_model_vasanth","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("qa_model_vasanth", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_model_vasanth|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/Vasanth/qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-qnli_microsoft_deberta_v3_base_seed_1_en.md b/docs/_posts/ahmedlone127/2024-09-08-qnli_microsoft_deberta_v3_base_seed_1_en.md
new file mode 100644
index 00000000000000..24836c05a73102
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-qnli_microsoft_deberta_v3_base_seed_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English qnli_microsoft_deberta_v3_base_seed_1 DeBertaForSequenceClassification from utahnlp
+author: John Snow Labs
+name: qnli_microsoft_deberta_v3_base_seed_1
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qnli_microsoft_deberta_v3_base_seed_1` is a English model originally trained by utahnlp.
+
+{:.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/qnli_microsoft_deberta_v3_base_seed_1_en_5.5.0_3.0_1725802931560.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qnli_microsoft_deberta_v3_base_seed_1_en_5.5.0_3.0_1725802931560.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("qnli_microsoft_deberta_v3_base_seed_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("qnli_microsoft_deberta_v3_base_seed_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qnli_microsoft_deberta_v3_base_seed_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|637.9 MB|
+
+## References
+
+https://huggingface.co/utahnlp/qnli_microsoft_deberta-v3-base_seed-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-qnli_microsoft_deberta_v3_base_seed_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-qnli_microsoft_deberta_v3_base_seed_1_pipeline_en.md
new file mode 100644
index 00000000000000..34fdda804c804e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-qnli_microsoft_deberta_v3_base_seed_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English qnli_microsoft_deberta_v3_base_seed_1_pipeline pipeline DeBertaForSequenceClassification from utahnlp
+author: John Snow Labs
+name: qnli_microsoft_deberta_v3_base_seed_1_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qnli_microsoft_deberta_v3_base_seed_1_pipeline` is a English model originally trained by utahnlp.
+
+{:.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/qnli_microsoft_deberta_v3_base_seed_1_pipeline_en_5.5.0_3.0_1725802983691.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qnli_microsoft_deberta_v3_base_seed_1_pipeline_en_5.5.0_3.0_1725802983691.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
+
+pipeline = PretrainedPipeline("qnli_microsoft_deberta_v3_base_seed_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qnli_microsoft_deberta_v3_base_seed_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qnli_microsoft_deberta_v3_base_seed_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|637.9 MB|
+
+## References
+
+https://huggingface.co/utahnlp/qnli_microsoft_deberta-v3-base_seed-1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-qnli_microsoft_deberta_v3_base_seed_2_en.md b/docs/_posts/ahmedlone127/2024-09-08-qnli_microsoft_deberta_v3_base_seed_2_en.md
new file mode 100644
index 00000000000000..5b2f31c91843f8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-qnli_microsoft_deberta_v3_base_seed_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English qnli_microsoft_deberta_v3_base_seed_2 DeBertaForSequenceClassification from utahnlp
+author: John Snow Labs
+name: qnli_microsoft_deberta_v3_base_seed_2
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qnli_microsoft_deberta_v3_base_seed_2` is a English model originally trained by utahnlp.
+
+{:.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/qnli_microsoft_deberta_v3_base_seed_2_en_5.5.0_3.0_1725812003982.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qnli_microsoft_deberta_v3_base_seed_2_en_5.5.0_3.0_1725812003982.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("qnli_microsoft_deberta_v3_base_seed_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("qnli_microsoft_deberta_v3_base_seed_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qnli_microsoft_deberta_v3_base_seed_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|637.9 MB|
+
+## References
+
+https://huggingface.co/utahnlp/qnli_microsoft_deberta-v3-base_seed-2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-qqp_microsoft_deberta_v3_base_seed_3_en.md b/docs/_posts/ahmedlone127/2024-09-08-qqp_microsoft_deberta_v3_base_seed_3_en.md
new file mode 100644
index 00000000000000..1ffca24949a112
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-qqp_microsoft_deberta_v3_base_seed_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English qqp_microsoft_deberta_v3_base_seed_3 DeBertaForSequenceClassification from utahnlp
+author: John Snow Labs
+name: qqp_microsoft_deberta_v3_base_seed_3
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qqp_microsoft_deberta_v3_base_seed_3` is a English model originally trained by utahnlp.
+
+{:.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/qqp_microsoft_deberta_v3_base_seed_3_en_5.5.0_3.0_1725803276398.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qqp_microsoft_deberta_v3_base_seed_3_en_5.5.0_3.0_1725803276398.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("qqp_microsoft_deberta_v3_base_seed_3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("qqp_microsoft_deberta_v3_base_seed_3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qqp_microsoft_deberta_v3_base_seed_3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|648.9 MB|
+
+## References
+
+https://huggingface.co/utahnlp/qqp_microsoft_deberta-v3-base_seed-3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-query_only_5_en.md b/docs/_posts/ahmedlone127/2024-09-08-query_only_5_en.md
new file mode 100644
index 00000000000000..c1462e08c25391
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-query_only_5_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English query_only_5 MPNetEmbeddings from ingeol
+author: John Snow Labs
+name: query_only_5
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`query_only_5` is a English model originally trained by ingeol.
+
+{:.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/query_only_5_en_5.5.0_3.0_1725817377530.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/query_only_5_en_5.5.0_3.0_1725817377530.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("query_only_5","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("query_only_5","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|query_only_5|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/ingeol/query_only_5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-query_relevance_distilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-query_relevance_distilbert_pipeline_en.md
new file mode 100644
index 00000000000000..9433ee05ad5557
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-query_relevance_distilbert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English query_relevance_distilbert_pipeline pipeline DistilBertForSequenceClassification from actuaryzhang
+author: John Snow Labs
+name: query_relevance_distilbert_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`query_relevance_distilbert_pipeline` is a English model originally trained by actuaryzhang.
+
+{:.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/query_relevance_distilbert_pipeline_en_5.5.0_3.0_1725777330199.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/query_relevance_distilbert_pipeline_en_5.5.0_3.0_1725777330199.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
+
+pipeline = PretrainedPipeline("query_relevance_distilbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("query_relevance_distilbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|query_relevance_distilbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/actuaryzhang/query-relevance-distilbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-question_answering_finetuned_tanzuhuggingface_en.md b/docs/_posts/ahmedlone127/2024-09-08-question_answering_finetuned_tanzuhuggingface_en.md
new file mode 100644
index 00000000000000..5eeb6c81e65b9f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-question_answering_finetuned_tanzuhuggingface_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English question_answering_finetuned_tanzuhuggingface DistilBertForQuestionAnswering from tanzuhuggingface
+author: John Snow Labs
+name: question_answering_finetuned_tanzuhuggingface
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`question_answering_finetuned_tanzuhuggingface` is a English model originally trained by tanzuhuggingface.
+
+{:.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/question_answering_finetuned_tanzuhuggingface_en_5.5.0_3.0_1725818109572.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/question_answering_finetuned_tanzuhuggingface_en_5.5.0_3.0_1725818109572.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("question_answering_finetuned_tanzuhuggingface","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("question_answering_finetuned_tanzuhuggingface", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|question_answering_finetuned_tanzuhuggingface|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/tanzuhuggingface/question-answering-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-question_answering_finetuned_tanzuhuggingface_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-question_answering_finetuned_tanzuhuggingface_pipeline_en.md
new file mode 100644
index 00000000000000..b147f9b0f565e4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-question_answering_finetuned_tanzuhuggingface_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English question_answering_finetuned_tanzuhuggingface_pipeline pipeline DistilBertForQuestionAnswering from tanzuhuggingface
+author: John Snow Labs
+name: question_answering_finetuned_tanzuhuggingface_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`question_answering_finetuned_tanzuhuggingface_pipeline` is a English model originally trained by tanzuhuggingface.
+
+{:.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/question_answering_finetuned_tanzuhuggingface_pipeline_en_5.5.0_3.0_1725818122278.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/question_answering_finetuned_tanzuhuggingface_pipeline_en_5.5.0_3.0_1725818122278.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
+
+pipeline = PretrainedPipeline("question_answering_finetuned_tanzuhuggingface_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("question_answering_finetuned_tanzuhuggingface_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|question_answering_finetuned_tanzuhuggingface_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/tanzuhuggingface/question-answering-finetuned
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-question_oriya_statement_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-question_oriya_statement_pipeline_en.md
new file mode 100644
index 00000000000000..852c7a113fd1d0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-question_oriya_statement_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English question_oriya_statement_pipeline pipeline RoBertaForSequenceClassification from nikolasmoya
+author: John Snow Labs
+name: question_oriya_statement_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`question_oriya_statement_pipeline` is a English model originally trained by nikolasmoya.
+
+{:.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/question_oriya_statement_pipeline_en_5.5.0_3.0_1725829948338.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/question_oriya_statement_pipeline_en_5.5.0_3.0_1725829948338.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
+
+pipeline = PretrainedPipeline("question_oriya_statement_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("question_oriya_statement_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|question_oriya_statement_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.7 MB|
+
+## References
+
+https://huggingface.co/nikolasmoya/question-or-statement
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-radiologoy_content_clasiffication_mlm_05_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-radiologoy_content_clasiffication_mlm_05_pipeline_en.md
new file mode 100644
index 00000000000000..b384bfaec0a77f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-radiologoy_content_clasiffication_mlm_05_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English radiologoy_content_clasiffication_mlm_05_pipeline pipeline BertForSequenceClassification from mtl-dev
+author: John Snow Labs
+name: radiologoy_content_clasiffication_mlm_05_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`radiologoy_content_clasiffication_mlm_05_pipeline` is a English model originally trained by mtl-dev.
+
+{:.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/radiologoy_content_clasiffication_mlm_05_pipeline_en_5.5.0_3.0_1725819412750.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/radiologoy_content_clasiffication_mlm_05_pipeline_en_5.5.0_3.0_1725819412750.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
+
+pipeline = PretrainedPipeline("radiologoy_content_clasiffication_mlm_05_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("radiologoy_content_clasiffication_mlm_05_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|radiologoy_content_clasiffication_mlm_05_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|414.4 MB|
+
+## References
+
+https://huggingface.co/mtl-dev/radiologoy_content_clasiffication_mlm_05
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-reason_en.md b/docs/_posts/ahmedlone127/2024-09-08-reason_en.md
new file mode 100644
index 00000000000000..ed35c25e91a9de
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-reason_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English reason BertForSequenceClassification from Mahmoud3899
+author: John Snow Labs
+name: reason
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`reason` is a English model originally trained by Mahmoud3899.
+
+{:.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/reason_en_5.5.0_3.0_1725802221225.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/reason_en_5.5.0_3.0_1725802221225.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("reason","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("reason", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|reason|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/Mahmoud3899/reason
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-reason_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-reason_pipeline_en.md
new file mode 100644
index 00000000000000..92afbd6cba506b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-reason_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English reason_pipeline pipeline BertForSequenceClassification from Mahmoud3899
+author: John Snow Labs
+name: reason_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`reason_pipeline` is a English model originally trained by Mahmoud3899.
+
+{:.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/reason_pipeline_en_5.5.0_3.0_1725802243245.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/reason_pipeline_en_5.5.0_3.0_1725802243245.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
+
+pipeline = PretrainedPipeline("reason_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("reason_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|reason_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/Mahmoud3899/reason
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-recipes_trainer_n_sentences_per_recipe_3_sep_true_en.md b/docs/_posts/ahmedlone127/2024-09-08-recipes_trainer_n_sentences_per_recipe_3_sep_true_en.md
new file mode 100644
index 00000000000000..df5210824bbac8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-recipes_trainer_n_sentences_per_recipe_3_sep_true_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English recipes_trainer_n_sentences_per_recipe_3_sep_true CamemBertEmbeddings from comartinez
+author: John Snow Labs
+name: recipes_trainer_n_sentences_per_recipe_3_sep_true
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`recipes_trainer_n_sentences_per_recipe_3_sep_true` is a English model originally trained by comartinez.
+
+{:.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/recipes_trainer_n_sentences_per_recipe_3_sep_true_en_5.5.0_3.0_1725836739213.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/recipes_trainer_n_sentences_per_recipe_3_sep_true_en_5.5.0_3.0_1725836739213.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("recipes_trainer_n_sentences_per_recipe_3_sep_true","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("recipes_trainer_n_sentences_per_recipe_3_sep_true","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|recipes_trainer_n_sentences_per_recipe_3_sep_true|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|412.3 MB|
+
+## References
+
+https://huggingface.co/comartinez/recipes-trainer_n_sentences_per_recipe_3_sep_True
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-refpydst_5p_icdst_split_v1_en.md b/docs/_posts/ahmedlone127/2024-09-08-refpydst_5p_icdst_split_v1_en.md
new file mode 100644
index 00000000000000..cadbd36478793f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-refpydst_5p_icdst_split_v1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English refpydst_5p_icdst_split_v1 MPNetEmbeddings from Brendan
+author: John Snow Labs
+name: refpydst_5p_icdst_split_v1
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`refpydst_5p_icdst_split_v1` is a English model originally trained by Brendan.
+
+{:.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/refpydst_5p_icdst_split_v1_en_5.5.0_3.0_1725815953861.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/refpydst_5p_icdst_split_v1_en_5.5.0_3.0_1725815953861.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("refpydst_5p_icdst_split_v1","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("refpydst_5p_icdst_split_v1","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|refpydst_5p_icdst_split_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/Brendan/refpydst-5p-icdst-split-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-results_maggiexshen_en.md b/docs/_posts/ahmedlone127/2024-09-08-results_maggiexshen_en.md
new file mode 100644
index 00000000000000..4c664076a78447
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-results_maggiexshen_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English results_maggiexshen RoBertaForSequenceClassification from MaggieXShen
+author: John Snow Labs
+name: results_maggiexshen
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_maggiexshen` is a English model originally trained by MaggieXShen.
+
+{:.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/results_maggiexshen_en_5.5.0_3.0_1725830851066.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_maggiexshen_en_5.5.0_3.0_1725830851066.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("results_maggiexshen","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("results_maggiexshen", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_maggiexshen|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|436.0 MB|
+
+## References
+
+https://huggingface.co/MaggieXShen/results
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-results_mdetry_en.md b/docs/_posts/ahmedlone127/2024-09-08-results_mdetry_en.md
new file mode 100644
index 00000000000000..b1c52e0f971a9d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-results_mdetry_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English results_mdetry DistilBertForQuestionAnswering from Mdetry
+author: John Snow Labs
+name: results_mdetry
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_mdetry` is a English model originally trained by Mdetry.
+
+{:.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/results_mdetry_en_5.5.0_3.0_1725823287128.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_mdetry_en_5.5.0_3.0_1725823287128.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("results_mdetry","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("results_mdetry", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_mdetry|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Mdetry/results
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-results_mdetry_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-results_mdetry_pipeline_en.md
new file mode 100644
index 00000000000000..63c5b5358bc638
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-results_mdetry_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English results_mdetry_pipeline pipeline DistilBertForQuestionAnswering from Mdetry
+author: John Snow Labs
+name: results_mdetry_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_mdetry_pipeline` is a English model originally trained by Mdetry.
+
+{:.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/results_mdetry_pipeline_en_5.5.0_3.0_1725823299677.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_mdetry_pipeline_en_5.5.0_3.0_1725823299677.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
+
+pipeline = PretrainedPipeline("results_mdetry_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("results_mdetry_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_mdetry_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Mdetry/results
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-results_yasminsur_en.md b/docs/_posts/ahmedlone127/2024-09-08-results_yasminsur_en.md
new file mode 100644
index 00000000000000..d864b2137fb965
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-results_yasminsur_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English results_yasminsur DistilBertForTokenClassification from yasminsur
+author: John Snow Labs
+name: results_yasminsur
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_yasminsur` is a English model originally trained by yasminsur.
+
+{:.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/results_yasminsur_en_5.5.0_3.0_1725827819868.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_yasminsur_en_5.5.0_3.0_1725827819868.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("results_yasminsur","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("results_yasminsur", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_yasminsur|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|505.5 MB|
+
+## References
+
+https://huggingface.co/yasminsur/results
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-results_yasminsur_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-results_yasminsur_pipeline_en.md
new file mode 100644
index 00000000000000..f4b80023515a69
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-results_yasminsur_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English results_yasminsur_pipeline pipeline DistilBertForTokenClassification from yasminsur
+author: John Snow Labs
+name: results_yasminsur_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_yasminsur_pipeline` is a English model originally trained by yasminsur.
+
+{:.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/results_yasminsur_pipeline_en_5.5.0_3.0_1725827844351.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_yasminsur_pipeline_en_5.5.0_3.0_1725827844351.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
+
+pipeline = PretrainedPipeline("results_yasminsur_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("results_yasminsur_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_yasminsur_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|505.6 MB|
+
+## References
+
+https://huggingface.co/yasminsur/results
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-rise_ner_distilbert_base_cased_system_a_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-rise_ner_distilbert_base_cased_system_a_v2_pipeline_en.md
new file mode 100644
index 00000000000000..5590309e01a25b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-rise_ner_distilbert_base_cased_system_a_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English rise_ner_distilbert_base_cased_system_a_v2_pipeline pipeline DistilBertForTokenClassification from petersamoaa
+author: John Snow Labs
+name: rise_ner_distilbert_base_cased_system_a_v2_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rise_ner_distilbert_base_cased_system_a_v2_pipeline` is a English model originally trained by petersamoaa.
+
+{:.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/rise_ner_distilbert_base_cased_system_a_v2_pipeline_en_5.5.0_3.0_1725788481916.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rise_ner_distilbert_base_cased_system_a_v2_pipeline_en_5.5.0_3.0_1725788481916.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
+
+pipeline = PretrainedPipeline("rise_ner_distilbert_base_cased_system_a_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rise_ner_distilbert_base_cased_system_a_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rise_ner_distilbert_base_cased_system_a_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.9 MB|
+
+## References
+
+https://huggingface.co/petersamoaa/rise-ner-distilbert-base-cased-system-a-v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-rmse_3_en.md b/docs/_posts/ahmedlone127/2024-09-08-rmse_3_en.md
new file mode 100644
index 00000000000000..a6b89e4b1fa992
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-rmse_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English rmse_3 RoBertaForSequenceClassification from BaronSch
+author: John Snow Labs
+name: rmse_3
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rmse_3` is a English model originally trained by BaronSch.
+
+{:.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/rmse_3_en_5.5.0_3.0_1725778477580.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rmse_3_en_5.5.0_3.0_1725778477580.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("rmse_3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("rmse_3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rmse_3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|468.5 MB|
+
+## References
+
+https://huggingface.co/BaronSch/RMSE_3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-rmse_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-rmse_3_pipeline_en.md
new file mode 100644
index 00000000000000..fd645981983edc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-rmse_3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English rmse_3_pipeline pipeline RoBertaForSequenceClassification from BaronSch
+author: John Snow Labs
+name: rmse_3_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rmse_3_pipeline` is a English model originally trained by BaronSch.
+
+{:.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/rmse_3_pipeline_en_5.5.0_3.0_1725778498721.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rmse_3_pipeline_en_5.5.0_3.0_1725778498721.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
+
+pipeline = PretrainedPipeline("rmse_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rmse_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rmse_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.5 MB|
+
+## References
+
+https://huggingface.co/BaronSch/RMSE_3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta2_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta2_en.md
new file mode 100644
index 00000000000000..40411a54752e9e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta2 RoBertaForSequenceClassification from sidd272
+author: John Snow Labs
+name: roberta2
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta2` is a English model originally trained by sidd272.
+
+{:.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/roberta2_en_5.5.0_3.0_1725830306158.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta2_en_5.5.0_3.0_1725830306158.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|432.3 MB|
+
+## References
+
+https://huggingface.co/sidd272/Roberta2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_augmented_finetuned_atis_3pct_v2_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_augmented_finetuned_atis_3pct_v2_en.md
new file mode 100644
index 00000000000000..9c42befbbfd44d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_augmented_finetuned_atis_3pct_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_augmented_finetuned_atis_3pct_v2 RoBertaForSequenceClassification from benayas
+author: John Snow Labs
+name: roberta_augmented_finetuned_atis_3pct_v2
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_augmented_finetuned_atis_3pct_v2` is a English model originally trained by benayas.
+
+{:.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/roberta_augmented_finetuned_atis_3pct_v2_en_5.5.0_3.0_1725829591282.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_augmented_finetuned_atis_3pct_v2_en_5.5.0_3.0_1725829591282.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta_augmented_finetuned_atis_3pct_v2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_augmented_finetuned_atis_3pct_v2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_augmented_finetuned_atis_3pct_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|424.9 MB|
+
+## References
+
+https://huggingface.co/benayas/roberta-augmented-finetuned-atis_3pct_v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_augmented_finetuned_atis_3pct_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_augmented_finetuned_atis_3pct_v2_pipeline_en.md
new file mode 100644
index 00000000000000..162ed978331681
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_augmented_finetuned_atis_3pct_v2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_augmented_finetuned_atis_3pct_v2_pipeline pipeline RoBertaForSequenceClassification from benayas
+author: John Snow Labs
+name: roberta_augmented_finetuned_atis_3pct_v2_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_augmented_finetuned_atis_3pct_v2_pipeline` is a English model originally trained by benayas.
+
+{:.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/roberta_augmented_finetuned_atis_3pct_v2_pipeline_en_5.5.0_3.0_1725829630531.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_augmented_finetuned_atis_3pct_v2_pipeline_en_5.5.0_3.0_1725829630531.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
+
+pipeline = PretrainedPipeline("roberta_augmented_finetuned_atis_3pct_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_augmented_finetuned_atis_3pct_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_augmented_finetuned_atis_3pct_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|425.0 MB|
+
+## References
+
+https://huggingface.co/benayas/roberta-augmented-finetuned-atis_3pct_v2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_base_bne_finetuned_amazon_reviews_multi_jorgemariocalvo_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_base_bne_finetuned_amazon_reviews_multi_jorgemariocalvo_en.md
new file mode 100644
index 00000000000000..cc9476423bc2f0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_base_bne_finetuned_amazon_reviews_multi_jorgemariocalvo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_bne_finetuned_amazon_reviews_multi_jorgemariocalvo RoBertaForSequenceClassification from jorgemariocalvo
+author: John Snow Labs
+name: roberta_base_bne_finetuned_amazon_reviews_multi_jorgemariocalvo
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_bne_finetuned_amazon_reviews_multi_jorgemariocalvo` is a English model originally trained by jorgemariocalvo.
+
+{:.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/roberta_base_bne_finetuned_amazon_reviews_multi_jorgemariocalvo_en_5.5.0_3.0_1725830924742.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_bne_finetuned_amazon_reviews_multi_jorgemariocalvo_en_5.5.0_3.0_1725830924742.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta_base_bne_finetuned_amazon_reviews_multi_jorgemariocalvo","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_bne_finetuned_amazon_reviews_multi_jorgemariocalvo", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_bne_finetuned_amazon_reviews_multi_jorgemariocalvo|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|446.8 MB|
+
+## References
+
+https://huggingface.co/jorgemariocalvo/roberta-base-bne-finetuned-amazon_reviews_multi
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_base_correlation_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_base_correlation_en.md
new file mode 100644
index 00000000000000..05e181a54c55eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_base_correlation_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_correlation RoBertaForSequenceClassification from Nared45
+author: John Snow Labs
+name: roberta_base_correlation
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_correlation` is a English model originally trained by Nared45.
+
+{:.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/roberta_base_correlation_en_5.5.0_3.0_1725830056284.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_correlation_en_5.5.0_3.0_1725830056284.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta_base_correlation","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_correlation", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_correlation|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|424.4 MB|
+
+## References
+
+https://huggingface.co/Nared45/roberta-base_correlation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_base_correlation_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_base_correlation_pipeline_en.md
new file mode 100644
index 00000000000000..07f5a71052cfb9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_base_correlation_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_correlation_pipeline pipeline RoBertaForSequenceClassification from Nared45
+author: John Snow Labs
+name: roberta_base_correlation_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_correlation_pipeline` is a English model originally trained by Nared45.
+
+{:.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/roberta_base_correlation_pipeline_en_5.5.0_3.0_1725830091495.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_correlation_pipeline_en_5.5.0_3.0_1725830091495.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
+
+pipeline = PretrainedPipeline("roberta_base_correlation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_correlation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_correlation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|424.5 MB|
+
+## References
+
+https://huggingface.co/Nared45/roberta-base_correlation
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_base_emolit_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_base_emolit_en.md
new file mode 100644
index 00000000000000..914ef287a4c6b0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_base_emolit_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_emolit RoBertaForSequenceClassification from lrei
+author: John Snow Labs
+name: roberta_base_emolit
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_emolit` is a English model originally trained by lrei.
+
+{:.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/roberta_base_emolit_en_5.5.0_3.0_1725830222481.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_emolit_en_5.5.0_3.0_1725830222481.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta_base_emolit","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_emolit", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_emolit|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|458.3 MB|
+
+## References
+
+https://huggingface.co/lrei/roberta-base-emolit
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_base_emolit_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_base_emolit_pipeline_en.md
new file mode 100644
index 00000000000000..5c2ec91df3b1f9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_base_emolit_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_emolit_pipeline pipeline RoBertaForSequenceClassification from lrei
+author: John Snow Labs
+name: roberta_base_emolit_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_emolit_pipeline` is a English model originally trained by lrei.
+
+{:.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/roberta_base_emolit_pipeline_en_5.5.0_3.0_1725830248760.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_emolit_pipeline_en_5.5.0_3.0_1725830248760.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
+
+pipeline = PretrainedPipeline("roberta_base_emolit_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_emolit_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_emolit_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|458.4 MB|
+
+## References
+
+https://huggingface.co/lrei/roberta-base-emolit
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_base_emotion_pysentimiento_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_base_emotion_pysentimiento_en.md
new file mode 100644
index 00000000000000..79c569a803ee69
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_base_emotion_pysentimiento_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_emotion_pysentimiento RoBertaForSequenceClassification from pysentimiento
+author: John Snow Labs
+name: roberta_base_emotion_pysentimiento
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_emotion_pysentimiento` is a English model originally trained by pysentimiento.
+
+{:.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/roberta_base_emotion_pysentimiento_en_5.5.0_3.0_1725778321656.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_emotion_pysentimiento_en_5.5.0_3.0_1725778321656.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta_base_emotion_pysentimiento","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_emotion_pysentimiento", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_emotion_pysentimiento|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|456.0 MB|
+
+## References
+
+https://huggingface.co/pysentimiento/roberta-base-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_base_ftd_on_glue_stsb_iter_5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_base_ftd_on_glue_stsb_iter_5_pipeline_en.md
new file mode 100644
index 00000000000000..66c738bd1442e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_base_ftd_on_glue_stsb_iter_5_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_ftd_on_glue_stsb_iter_5_pipeline pipeline RoBertaForSequenceClassification from Ibrahim-Alam
+author: John Snow Labs
+name: roberta_base_ftd_on_glue_stsb_iter_5_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_ftd_on_glue_stsb_iter_5_pipeline` is a English model originally trained by Ibrahim-Alam.
+
+{:.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/roberta_base_ftd_on_glue_stsb_iter_5_pipeline_en_5.5.0_3.0_1725778875853.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_ftd_on_glue_stsb_iter_5_pipeline_en_5.5.0_3.0_1725778875853.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
+
+pipeline = PretrainedPipeline("roberta_base_ftd_on_glue_stsb_iter_5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_ftd_on_glue_stsb_iter_5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_ftd_on_glue_stsb_iter_5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|444.5 MB|
+
+## References
+
+https://huggingface.co/Ibrahim-Alam/roberta-base_FTd_on_glue-stsb_iter-5
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_base_prop_16_train_set_michaellutz_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_base_prop_16_train_set_michaellutz_en.md
new file mode 100644
index 00000000000000..e81eb3fac6d8a0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_base_prop_16_train_set_michaellutz_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_base_prop_16_train_set_michaellutz RoBertaForSequenceClassification from michaellutz
+author: John Snow Labs
+name: roberta_base_prop_16_train_set_michaellutz
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_prop_16_train_set_michaellutz` is a English model originally trained by michaellutz.
+
+{:.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/roberta_base_prop_16_train_set_michaellutz_en_5.5.0_3.0_1725820580140.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_prop_16_train_set_michaellutz_en_5.5.0_3.0_1725820580140.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta_base_prop_16_train_set_michaellutz","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_base_prop_16_train_set_michaellutz", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_prop_16_train_set_michaellutz|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|417.4 MB|
+
+## References
+
+https://huggingface.co/michaellutz/roberta-base-prop-16-train-set
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_base_prop_16_train_set_michaellutz_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_base_prop_16_train_set_michaellutz_pipeline_en.md
new file mode 100644
index 00000000000000..15e002722c7dba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_base_prop_16_train_set_michaellutz_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_base_prop_16_train_set_michaellutz_pipeline pipeline RoBertaForSequenceClassification from michaellutz
+author: John Snow Labs
+name: roberta_base_prop_16_train_set_michaellutz_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_prop_16_train_set_michaellutz_pipeline` is a English model originally trained by michaellutz.
+
+{:.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/roberta_base_prop_16_train_set_michaellutz_pipeline_en_5.5.0_3.0_1725820622524.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_prop_16_train_set_michaellutz_pipeline_en_5.5.0_3.0_1725820622524.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
+
+pipeline = PretrainedPipeline("roberta_base_prop_16_train_set_michaellutz_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_prop_16_train_set_michaellutz_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_prop_16_train_set_michaellutz_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|417.4 MB|
+
+## References
+
+https://huggingface.co/michaellutz/roberta-base-prop-16-train-set
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_base_squad2_deepset_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_base_squad2_deepset_en.md
new file mode 100644
index 00000000000000..bebfd0f0e19a9b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_base_squad2_deepset_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English roberta_base_squad2_deepset RoBertaForQuestionAnswering from djovak
+author: John Snow Labs
+name: roberta_base_squad2_deepset
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_squad2_deepset` is a English model originally trained by djovak.
+
+{:.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/roberta_base_squad2_deepset_en_5.5.0_3.0_1725833695683.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_squad2_deepset_en_5.5.0_3.0_1725833695683.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_base_squad2_deepset","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_base_squad2_deepset", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_squad2_deepset|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|463.5 MB|
+
+## References
+
+https://huggingface.co/djovak/roberta-base-squad2-deepset
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_base_squad2_finetuned_custom_ds_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_base_squad2_finetuned_custom_ds_pipeline_en.md
new file mode 100644
index 00000000000000..a961ccd966c7df
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_base_squad2_finetuned_custom_ds_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_base_squad2_finetuned_custom_ds_pipeline pipeline RoBertaForQuestionAnswering from ngchuchi
+author: John Snow Labs
+name: roberta_base_squad2_finetuned_custom_ds_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_squad2_finetuned_custom_ds_pipeline` is a English model originally trained by ngchuchi.
+
+{:.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/roberta_base_squad2_finetuned_custom_ds_pipeline_en_5.5.0_3.0_1725833204081.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_squad2_finetuned_custom_ds_pipeline_en_5.5.0_3.0_1725833204081.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
+
+pipeline = PretrainedPipeline("roberta_base_squad2_finetuned_custom_ds_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_squad2_finetuned_custom_ds_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_squad2_finetuned_custom_ds_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.5 MB|
+
+## References
+
+https://huggingface.co/ngchuchi/roberta-base-squad2-finetuned-custom-ds
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_books_wiki_bpe_47k_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_books_wiki_bpe_47k_en.md
new file mode 100644
index 00000000000000..ebe8f13f3dc54e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_books_wiki_bpe_47k_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_books_wiki_bpe_47k CamemBertEmbeddings from nfliu
+author: John Snow Labs
+name: roberta_books_wiki_bpe_47k
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_books_wiki_bpe_47k` is a English model originally trained by nfliu.
+
+{:.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/roberta_books_wiki_bpe_47k_en_5.5.0_3.0_1725787912801.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_books_wiki_bpe_47k_en_5.5.0_3.0_1725787912801.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("roberta_books_wiki_bpe_47k","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("roberta_books_wiki_bpe_47k","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_books_wiki_bpe_47k|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|272.1 MB|
+
+## References
+
+https://huggingface.co/nfliu/roberta_books_wiki_bpe_47k
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_books_wiki_bpe_47k_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_books_wiki_bpe_47k_pipeline_en.md
new file mode 100644
index 00000000000000..d0b7caaa0b5d24
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_books_wiki_bpe_47k_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_books_wiki_bpe_47k_pipeline pipeline CamemBertEmbeddings from nfliu
+author: John Snow Labs
+name: roberta_books_wiki_bpe_47k_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_books_wiki_bpe_47k_pipeline` is a English model originally trained by nfliu.
+
+{:.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/roberta_books_wiki_bpe_47k_pipeline_en_5.5.0_3.0_1725787987635.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_books_wiki_bpe_47k_pipeline_en_5.5.0_3.0_1725787987635.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
+
+pipeline = PretrainedPipeline("roberta_books_wiki_bpe_47k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_books_wiki_bpe_47k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_books_wiki_bpe_47k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|272.1 MB|
+
+## References
+
+https://huggingface.co/nfliu/roberta_books_wiki_bpe_47k
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_chinese_sensible_zh.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_chinese_sensible_zh.md
new file mode 100644
index 00000000000000..e86d3f0dcc275b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_chinese_sensible_zh.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Chinese roberta_chinese_sensible BertForSequenceClassification from thu-coai
+author: John Snow Labs
+name: roberta_chinese_sensible
+date: 2024-09-08
+tags: [zh, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: zh
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_chinese_sensible` is a Chinese model originally trained by thu-coai.
+
+{:.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/roberta_chinese_sensible_zh_5.5.0_3.0_1725838655571.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_chinese_sensible_zh_5.5.0_3.0_1725838655571.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("roberta_chinese_sensible","zh") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("roberta_chinese_sensible", "zh")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_chinese_sensible|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|zh|
+|Size:|383.3 MB|
+
+## References
+
+https://huggingface.co/thu-coai/roberta-zh-sensible
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_crypto_profiling_task1_3_10_epochs_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_crypto_profiling_task1_3_10_epochs_pipeline_en.md
new file mode 100644
index 00000000000000..9829a24e46e6c9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_crypto_profiling_task1_3_10_epochs_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_crypto_profiling_task1_3_10_epochs_pipeline pipeline RoBertaForSequenceClassification from pabagcha
+author: John Snow Labs
+name: roberta_crypto_profiling_task1_3_10_epochs_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_crypto_profiling_task1_3_10_epochs_pipeline` is a English model originally trained by pabagcha.
+
+{:.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/roberta_crypto_profiling_task1_3_10_epochs_pipeline_en_5.5.0_3.0_1725830019634.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_crypto_profiling_task1_3_10_epochs_pipeline_en_5.5.0_3.0_1725830019634.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
+
+pipeline = PretrainedPipeline("roberta_crypto_profiling_task1_3_10_epochs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_crypto_profiling_task1_3_10_epochs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_crypto_profiling_task1_3_10_epochs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/pabagcha/roberta_crypto_profiling_task1_3_10_epochs
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_fine_tuned_on_newsmstc_02_split_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_fine_tuned_on_newsmstc_02_split_pipeline_en.md
new file mode 100644
index 00000000000000..1e7d34bc0af82e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_fine_tuned_on_newsmstc_02_split_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_fine_tuned_on_newsmstc_02_split_pipeline pipeline RoBertaForSequenceClassification from MaxG1
+author: John Snow Labs
+name: roberta_fine_tuned_on_newsmstc_02_split_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_fine_tuned_on_newsmstc_02_split_pipeline` is a English model originally trained by MaxG1.
+
+{:.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/roberta_fine_tuned_on_newsmstc_02_split_pipeline_en_5.5.0_3.0_1725778765540.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_fine_tuned_on_newsmstc_02_split_pipeline_en_5.5.0_3.0_1725778765540.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
+
+pipeline = PretrainedPipeline("roberta_fine_tuned_on_newsmstc_02_split_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_fine_tuned_on_newsmstc_02_split_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_fine_tuned_on_newsmstc_02_split_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|445.0 MB|
+
+## References
+
+https://huggingface.co/MaxG1/roberta_fine_tuned_on_newsmstc_02_split
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_finetune_model_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_finetune_model_en.md
new file mode 100644
index 00000000000000..9ff96b546c583f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_finetune_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_finetune_model RoBertaForSequenceClassification from sandeep12345
+author: John Snow Labs
+name: roberta_finetune_model
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetune_model` is a English model originally trained by sandeep12345.
+
+{:.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/roberta_finetune_model_en_5.5.0_3.0_1725821456705.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetune_model_en_5.5.0_3.0_1725821456705.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta_finetune_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_finetune_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_finetune_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|449.9 MB|
+
+## References
+
+https://huggingface.co/sandeep12345/roberta_finetune_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_large_squadv2_titanbot_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_large_squadv2_titanbot_en.md
new file mode 100644
index 00000000000000..239c4b9f083c9c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_large_squadv2_titanbot_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English roberta_large_squadv2_titanbot RoBertaForQuestionAnswering from titanbot
+author: John Snow Labs
+name: roberta_large_squadv2_titanbot
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_squadv2_titanbot` is a English model originally trained by titanbot.
+
+{:.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/roberta_large_squadv2_titanbot_en_5.5.0_3.0_1725834264568.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_squadv2_titanbot_en_5.5.0_3.0_1725834264568.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_large_squadv2_titanbot","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_large_squadv2_titanbot", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_squadv2_titanbot|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/titanbot/Roberta-Large-SQUADV2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_large_squadv2_titanbot_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_large_squadv2_titanbot_pipeline_en.md
new file mode 100644
index 00000000000000..5a3872bd9fecde
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_large_squadv2_titanbot_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_large_squadv2_titanbot_pipeline pipeline RoBertaForQuestionAnswering from titanbot
+author: John Snow Labs
+name: roberta_large_squadv2_titanbot_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_squadv2_titanbot_pipeline` is a English model originally trained by titanbot.
+
+{:.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/roberta_large_squadv2_titanbot_pipeline_en_5.5.0_3.0_1725834330240.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_squadv2_titanbot_pipeline_en_5.5.0_3.0_1725834330240.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
+
+pipeline = PretrainedPipeline("roberta_large_squadv2_titanbot_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_large_squadv2_titanbot_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_squadv2_titanbot_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/titanbot/Roberta-Large-SQUADV2
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmented_english_xx.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmented_english_xx.md
new file mode 100644
index 00000000000000..06f15faf55f68f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmented_english_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmented_english RoBertaForTokenClassification from StivenLancheros
+author: John Snow Labs
+name: roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmented_english
+date: 2024-09-08
+tags: [xx, open_source, onnx, token_classification, roberta, ner]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmented_english` is a Multilingual model originally trained by StivenLancheros.
+
+{:.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/roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmented_english_xx_5.5.0_3.0_1725794192529.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmented_english_xx_5.5.0_3.0_1725794192529.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = RoBertaForTokenClassification.pretrained("roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmented_english","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmented_english", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_ner_roberta_base_biomedical_clinical_spanish_finetuned_ner_craft_augmented_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|xx|
+|Size:|438.7 MB|
+
+## References
+
+https://huggingface.co/StivenLancheros/roberta-base-biomedical-clinical-es-finetuned-ner-CRAFT_Augmented_EN
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_qa_QA_for_Event_Extraction_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_qa_QA_for_Event_Extraction_pipeline_en.md
new file mode 100644
index 00000000000000..729239921c98e3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_qa_QA_for_Event_Extraction_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_QA_for_Event_Extraction_pipeline pipeline RoBertaForQuestionAnswering from veronica320
+author: John Snow Labs
+name: roberta_qa_QA_for_Event_Extraction_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_QA_for_Event_Extraction_pipeline` is a English model originally trained by veronica320.
+
+{:.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/roberta_qa_QA_for_Event_Extraction_pipeline_en_5.5.0_3.0_1725757587887.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_QA_for_Event_Extraction_pipeline_en_5.5.0_3.0_1725757587887.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
+
+pipeline = PretrainedPipeline("roberta_qa_QA_for_Event_Extraction_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_QA_for_Event_Extraction_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_QA_for_Event_Extraction_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/veronica320/QA-for-Event-Extraction
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_qa_base_squad_pipeline_nl.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_qa_base_squad_pipeline_nl.md
new file mode 100644
index 00000000000000..8c6344803eab20
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_qa_base_squad_pipeline_nl.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Dutch, Flemish roberta_qa_base_squad_pipeline pipeline RoBertaForQuestionAnswering from Nadav
+author: John Snow Labs
+name: roberta_qa_base_squad_pipeline
+date: 2024-09-08
+tags: [nl, open_source, pipeline, onnx]
+task: Question Answering
+language: nl
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_base_squad_pipeline` is a Dutch, Flemish model originally trained by Nadav.
+
+{:.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/roberta_qa_base_squad_pipeline_nl_5.5.0_3.0_1725833505945.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_base_squad_pipeline_nl_5.5.0_3.0_1725833505945.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
+
+pipeline = PretrainedPipeline("roberta_qa_base_squad_pipeline", lang = "nl")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_base_squad_pipeline", lang = "nl")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_base_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|nl|
+|Size:|435.7 MB|
+
+## References
+
+https://huggingface.co/Nadav/roberta-base-squad-nl
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_qa_cline_techqa_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_qa_cline_techqa_en.md
new file mode 100644
index 00000000000000..59a67afb7536f6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_qa_cline_techqa_en.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering (from AnonymousSub)
+author: John Snow Labs
+name: roberta_qa_cline_techqa
+date: 2024-09-08
+tags: [en, open_source, question_answering, roberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `cline-techqa` is a English model originally trained by `AnonymousSub`.
+
+## 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/roberta_qa_cline_techqa_en_5.5.0_3.0_1725757427858.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_cline_techqa_en_5.5.0_3.0_1725757427858.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 = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_cline_techqa","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = RoBertaForQuestionAnswering
+.pretrained("roberta_qa_cline_techqa","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.roberta.techqa_cline.by_AnonymousSub").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_cline_techqa|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|465.6 MB|
+
+## References
+
+References
+
+- https://huggingface.co/AnonymousSub/cline-techqa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_qa_cline_techqa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_qa_cline_techqa_pipeline_en.md
new file mode 100644
index 00000000000000..5cbbedea39c5d3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_qa_cline_techqa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_cline_techqa_pipeline pipeline RoBertaForQuestionAnswering from AnonymousSub
+author: John Snow Labs
+name: roberta_qa_cline_techqa_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_cline_techqa_pipeline` is a English model originally trained by AnonymousSub.
+
+{:.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/roberta_qa_cline_techqa_pipeline_en_5.5.0_3.0_1725757449564.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_cline_techqa_pipeline_en_5.5.0_3.0_1725757449564.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
+
+pipeline = PretrainedPipeline("roberta_qa_cline_techqa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_cline_techqa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_cline_techqa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|465.6 MB|
+
+## References
+
+https://huggingface.co/AnonymousSub/cline-techqa
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_qa_declutr_model_squad2.0_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_qa_declutr_model_squad2.0_en.md
new file mode 100644
index 00000000000000..464b6cf1804f07
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_qa_declutr_model_squad2.0_en.md
@@ -0,0 +1,106 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering (from AnonymousSub)
+author: John Snow Labs
+name: roberta_qa_declutr_model_squad2.0
+date: 2024-09-08
+tags: [en, open_source, question_answering, roberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `declutr-model_squad2.0` is a English model originally trained by `AnonymousSub`.
+
+## 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/roberta_qa_declutr_model_squad2.0_en_5.5.0_3.0_1725834215961.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_declutr_model_squad2.0_en_5.5.0_3.0_1725834215961.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 = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_declutr_model_squad2.0","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = RoBertaForQuestionAnswering
+.pretrained("roberta_qa_declutr_model_squad2.0","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squadv2.roberta.declutr.by_AnonymousSub").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_declutr_model_squad2.0|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|306.8 MB|
+
+## References
+
+References
+
+- https://huggingface.co/AnonymousSub/declutr-model_squad2.0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_qa_declutr_model_squad2.0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_qa_declutr_model_squad2.0_pipeline_en.md
new file mode 100644
index 00000000000000..e1443df6d09fc5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_qa_declutr_model_squad2.0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_declutr_model_squad2.0_pipeline pipeline RoBertaForQuestionAnswering from AnonymousSub
+author: John Snow Labs
+name: roberta_qa_declutr_model_squad2.0_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_declutr_model_squad2.0_pipeline` is a English model originally trained by AnonymousSub.
+
+{:.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/roberta_qa_declutr_model_squad2.0_pipeline_en_5.5.0_3.0_1725834229958.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_declutr_model_squad2.0_pipeline_en_5.5.0_3.0_1725834229958.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
+
+pipeline = PretrainedPipeline("roberta_qa_declutr_model_squad2.0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_declutr_model_squad2.0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_declutr_model_squad2.0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|306.9 MB|
+
+## References
+
+https://huggingface.co/AnonymousSub/declutr-model_squad2.0
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_qa_finetuned_facility_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_qa_finetuned_facility_en.md
new file mode 100644
index 00000000000000..2dfc91ab3a40c4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_qa_finetuned_facility_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering Cased model (from skandaonsolve)
+author: John Snow Labs
+name: roberta_qa_finetuned_facility
+date: 2024-09-08
+tags: [en, open_source, roberta, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RobertaForQuestionAnswering  model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-finetuned-facility` is a English model originally trained by `skandaonsolve`.
+
+## 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/roberta_qa_finetuned_facility_en_5.5.0_3.0_1725833613224.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_finetuned_facility_en_5.5.0_3.0_1725833613224.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 = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_finetuned_facility","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_finetuned_facility","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_finetuned_facility|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|463.7 MB|
+
+## References
+
+References
+
+- https://huggingface.co/skandaonsolve/roberta-finetuned-facility
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_qa_roberta_base_finetuned_scrambled_squad_5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_qa_roberta_base_finetuned_scrambled_squad_5_pipeline_en.md
new file mode 100644
index 00000000000000..86622060c40d8f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_qa_roberta_base_finetuned_scrambled_squad_5_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_roberta_base_finetuned_scrambled_squad_5_pipeline pipeline RoBertaForQuestionAnswering from huxxx657
+author: John Snow Labs
+name: roberta_qa_roberta_base_finetuned_scrambled_squad_5_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_roberta_base_finetuned_scrambled_squad_5_pipeline` is a English model originally trained by huxxx657.
+
+{:.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/roberta_qa_roberta_base_finetuned_scrambled_squad_5_pipeline_en_5.5.0_3.0_1725757353441.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_finetuned_scrambled_squad_5_pipeline_en_5.5.0_3.0_1725757353441.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
+
+pipeline = PretrainedPipeline("roberta_qa_roberta_base_finetuned_scrambled_squad_5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_roberta_base_finetuned_scrambled_squad_5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_roberta_base_finetuned_scrambled_squad_5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.3 MB|
+
+## References
+
+https://huggingface.co/huxxx657/roberta-base-finetuned-scrambled-squad-5
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_qa_roberta_base_squad_v1_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_qa_roberta_base_squad_v1_en.md
new file mode 100644
index 00000000000000..5ada7ed9e6a095
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_qa_roberta_base_squad_v1_en.md
@@ -0,0 +1,111 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering (from csarron)
+author: John Snow Labs
+name: roberta_qa_roberta_base_squad_v1
+date: 2024-09-08
+tags: [en, open_source, question_answering, roberta, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-base-squad-v1` is a English model originally trained by `csarron`.
+
+## 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/roberta_qa_roberta_base_squad_v1_en_5.5.0_3.0_1725834102179.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_squad_v1_en_5.5.0_3.0_1725834102179.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 = MultiDocumentAssembler() \ 
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_roberta_base_squad_v1","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer") \
+.setCaseSensitive(True)
+
+pipeline = Pipeline().setStages([
+document_assembler,
+spanClassifier
+])
+
+example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(example).transform(example)
+```
+```scala
+val document = new MultiDocumentAssembler()
+.setInputCols("question", "context")
+.setOutputCols("document_question", "document_context")
+
+val spanClassifier = RoBertaForQuestionAnswering
+.pretrained("roberta_qa_roberta_base_squad_v1","en")
+.setInputCols(Array("document_question", "document_context"))
+.setOutputCol("answer")
+.setCaseSensitive(true)
+.setMaxSentenceLength(512)
+
+val pipeline = new Pipeline().setStages(Array(document, spanClassifier))
+
+val example = Seq(
+("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
+("What's my name?", "My name is Clara and I live in Berkeley."))
+.toDF("question", "context")
+
+val result = pipeline.fit(example).transform(example)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.roberta.base.by_csarron").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_roberta_base_squad_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|457.2 MB|
+
+## References
+
+References
+
+- https://huggingface.co/csarron/roberta-base-squad-v1
+- https://github.com/csarron
+- https://arxiv.org/abs/1907.11692
+- https://awk.ai/
+- https://twitter.com/sysnlp
+- https://rajpurkar.github.io/SQuAD-explorer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_qa_roberta_base_squad_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_qa_roberta_base_squad_v1_pipeline_en.md
new file mode 100644
index 00000000000000..f7c97c4e9cea44
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_qa_roberta_base_squad_v1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_roberta_base_squad_v1_pipeline pipeline RoBertaForQuestionAnswering from csarron
+author: John Snow Labs
+name: roberta_qa_roberta_base_squad_v1_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_roberta_base_squad_v1_pipeline` is a English model originally trained by csarron.
+
+{:.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/roberta_qa_roberta_base_squad_v1_pipeline_en_5.5.0_3.0_1725834127698.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_roberta_base_squad_v1_pipeline_en_5.5.0_3.0_1725834127698.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
+
+pipeline = PretrainedPipeline("roberta_qa_roberta_base_squad_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_roberta_base_squad_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_roberta_base_squad_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|457.2 MB|
+
+## References
+
+https://huggingface.co/csarron/roberta-base-squad-v1
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_qoura_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_qoura_en.md
new file mode 100644
index 00000000000000..d331aaae9d1f59
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_qoura_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English roberta_qoura RoBertaForQuestionAnswering from YasirAbdali
+author: John Snow Labs
+name: roberta_qoura
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qoura` is a English model originally trained by YasirAbdali.
+
+{:.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/roberta_qoura_en_5.5.0_3.0_1725833373822.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qoura_en_5.5.0_3.0_1725833373822.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qoura","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qoura", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qoura|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|465.2 MB|
+
+## References
+
+https://huggingface.co/YasirAbdali/roberta_qoura
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_soft_hd_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_soft_hd_pipeline_en.md
new file mode 100644
index 00000000000000..881fca4363f68c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_soft_hd_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_soft_hd_pipeline pipeline RoBertaForSequenceClassification from Multiperspective
+author: John Snow Labs
+name: roberta_soft_hd_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_soft_hd_pipeline` is a English model originally trained by Multiperspective.
+
+{:.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/roberta_soft_hd_pipeline_en_5.5.0_3.0_1725821330850.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_soft_hd_pipeline_en_5.5.0_3.0_1725821330850.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
+
+pipeline = PretrainedPipeline("roberta_soft_hd_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_soft_hd_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_soft_hd_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Multiperspective/roberta-soft-hd
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_soft_llm_multip_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_soft_llm_multip_en.md
new file mode 100644
index 00000000000000..0e028ea8949e84
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_soft_llm_multip_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_soft_llm_multip RoBertaForSequenceClassification from Multiperspective
+author: John Snow Labs
+name: roberta_soft_llm_multip
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_soft_llm_multip` is a English model originally trained by Multiperspective.
+
+{:.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/roberta_soft_llm_multip_en_5.5.0_3.0_1725778334620.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_soft_llm_multip_en_5.5.0_3.0_1725778334620.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta_soft_llm_multip","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_soft_llm_multip", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_soft_llm_multip|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/Multiperspective/roberta-soft-llm_multip
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_twitter_tickers_finetuned_2_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_twitter_tickers_finetuned_2_en.md
new file mode 100644
index 00000000000000..a9cb461736f027
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_twitter_tickers_finetuned_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_twitter_tickers_finetuned_2 RoBertaForSequenceClassification from Doom631
+author: John Snow Labs
+name: roberta_twitter_tickers_finetuned_2
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_twitter_tickers_finetuned_2` is a English model originally trained by Doom631.
+
+{:.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/roberta_twitter_tickers_finetuned_2_en_5.5.0_3.0_1725821545346.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_twitter_tickers_finetuned_2_en_5.5.0_3.0_1725821545346.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("roberta_twitter_tickers_finetuned_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_twitter_tickers_finetuned_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_twitter_tickers_finetuned_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|419.3 MB|
+
+## References
+
+https://huggingface.co/Doom631/Roberta_Twitter_Tickers_Finetuned_2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-roberta_twitter_tickers_finetuned_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-roberta_twitter_tickers_finetuned_2_pipeline_en.md
new file mode 100644
index 00000000000000..df314f0b17b10d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-roberta_twitter_tickers_finetuned_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English roberta_twitter_tickers_finetuned_2_pipeline pipeline RoBertaForSequenceClassification from Doom631
+author: John Snow Labs
+name: roberta_twitter_tickers_finetuned_2_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_twitter_tickers_finetuned_2_pipeline` is a English model originally trained by Doom631.
+
+{:.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/roberta_twitter_tickers_finetuned_2_pipeline_en_5.5.0_3.0_1725821583503.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_twitter_tickers_finetuned_2_pipeline_en_5.5.0_3.0_1725821583503.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
+
+pipeline = PretrainedPipeline("roberta_twitter_tickers_finetuned_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_twitter_tickers_finetuned_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_twitter_tickers_finetuned_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|419.3 MB|
+
+## References
+
+https://huggingface.co/Doom631/Roberta_Twitter_Tickers_Finetuned_2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-rotten_tomatoes_microsoft_deberta_v3_base_seed_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-rotten_tomatoes_microsoft_deberta_v3_base_seed_1_pipeline_en.md
new file mode 100644
index 00000000000000..ec4b7bfa699011
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-rotten_tomatoes_microsoft_deberta_v3_base_seed_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English rotten_tomatoes_microsoft_deberta_v3_base_seed_1_pipeline pipeline DeBertaForSequenceClassification from utahnlp
+author: John Snow Labs
+name: rotten_tomatoes_microsoft_deberta_v3_base_seed_1_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rotten_tomatoes_microsoft_deberta_v3_base_seed_1_pipeline` is a English model originally trained by utahnlp.
+
+{:.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/rotten_tomatoes_microsoft_deberta_v3_base_seed_1_pipeline_en_5.5.0_3.0_1725803030771.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rotten_tomatoes_microsoft_deberta_v3_base_seed_1_pipeline_en_5.5.0_3.0_1725803030771.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
+
+pipeline = PretrainedPipeline("rotten_tomatoes_microsoft_deberta_v3_base_seed_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rotten_tomatoes_microsoft_deberta_v3_base_seed_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rotten_tomatoes_microsoft_deberta_v3_base_seed_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|577.9 MB|
+
+## References
+
+https://huggingface.co/utahnlp/rotten_tomatoes_microsoft_deberta-v3-base_seed-1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-rulebert_v0_4_k0_it.md b/docs/_posts/ahmedlone127/2024-09-08-rulebert_v0_4_k0_it.md
new file mode 100644
index 00000000000000..4ea480e7fca7ec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-rulebert_v0_4_k0_it.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Italian rulebert_v0_4_k0 XlmRoBertaForSequenceClassification from ribesstefano
+author: John Snow Labs
+name: rulebert_v0_4_k0
+date: 2024-09-08
+tags: [it, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: it
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rulebert_v0_4_k0` is a Italian model originally trained by ribesstefano.
+
+{:.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/rulebert_v0_4_k0_it_5.5.0_3.0_1725779967261.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rulebert_v0_4_k0_it_5.5.0_3.0_1725779967261.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("rulebert_v0_4_k0","it") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("rulebert_v0_4_k0", "it")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rulebert_v0_4_k0|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|it|
+|Size:|870.4 MB|
+
+## References
+
+https://huggingface.co/ribesstefano/RuleBert-v0.4-k0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-russian_sentiment_classification_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-russian_sentiment_classification_model_pipeline_en.md
new file mode 100644
index 00000000000000..ee9aa643e6cd42
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-russian_sentiment_classification_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English russian_sentiment_classification_model_pipeline pipeline BertForSequenceClassification from annavtkn
+author: John Snow Labs
+name: russian_sentiment_classification_model_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`russian_sentiment_classification_model_pipeline` is a English model originally trained by annavtkn.
+
+{:.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/russian_sentiment_classification_model_pipeline_en_5.5.0_3.0_1725826014187.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/russian_sentiment_classification_model_pipeline_en_5.5.0_3.0_1725826014187.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
+
+pipeline = PretrainedPipeline("russian_sentiment_classification_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("russian_sentiment_classification_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|russian_sentiment_classification_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|666.5 MB|
+
+## References
+
+https://huggingface.co/annavtkn/ru_sentiment_classification_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sanskrit_saskta_qna_en.md b/docs/_posts/ahmedlone127/2024-09-08-sanskrit_saskta_qna_en.md
new file mode 100644
index 00000000000000..b2b584a9830d7c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sanskrit_saskta_qna_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English sanskrit_saskta_qna DistilBertForQuestionAnswering from Sachinkelenjaguri
+author: John Snow Labs
+name: sanskrit_saskta_qna
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sanskrit_saskta_qna` is a English model originally trained by Sachinkelenjaguri.
+
+{:.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/sanskrit_saskta_qna_en_5.5.0_3.0_1725798120126.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sanskrit_saskta_qna_en_5.5.0_3.0_1725798120126.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("sanskrit_saskta_qna","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("sanskrit_saskta_qna", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sanskrit_saskta_qna|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|248.0 MB|
+
+## References
+
+https://huggingface.co/Sachinkelenjaguri/sa_Qna
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sarcasm_detection_bert_base_uncased_en.md b/docs/_posts/ahmedlone127/2024-09-08-sarcasm_detection_bert_base_uncased_en.md
new file mode 100644
index 00000000000000..11dd530b9fce44
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sarcasm_detection_bert_base_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sarcasm_detection_bert_base_uncased BertForSequenceClassification from jkhan447
+author: John Snow Labs
+name: sarcasm_detection_bert_base_uncased
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sarcasm_detection_bert_base_uncased` is a English model originally trained by jkhan447.
+
+{:.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/sarcasm_detection_bert_base_uncased_en_5.5.0_3.0_1725802383401.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sarcasm_detection_bert_base_uncased_en_5.5.0_3.0_1725802383401.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("sarcasm_detection_bert_base_uncased","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("sarcasm_detection_bert_base_uncased", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sarcasm_detection_bert_base_uncased|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/jkhan447/sarcasm-detection-Bert-base-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sbert_russian_sentiment_rureviews_pipeline_ru.md b/docs/_posts/ahmedlone127/2024-09-08-sbert_russian_sentiment_rureviews_pipeline_ru.md
new file mode 100644
index 00000000000000..07cfff9e92200d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sbert_russian_sentiment_rureviews_pipeline_ru.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Russian sbert_russian_sentiment_rureviews_pipeline pipeline BertForSequenceClassification from sismetanin
+author: John Snow Labs
+name: sbert_russian_sentiment_rureviews_pipeline
+date: 2024-09-08
+tags: [ru, open_source, pipeline, onnx]
+task: Text Classification
+language: ru
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sbert_russian_sentiment_rureviews_pipeline` is a Russian model originally trained by sismetanin.
+
+{:.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/sbert_russian_sentiment_rureviews_pipeline_ru_5.5.0_3.0_1725819489812.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sbert_russian_sentiment_rureviews_pipeline_ru_5.5.0_3.0_1725819489812.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
+
+pipeline = PretrainedPipeline("sbert_russian_sentiment_rureviews_pipeline", lang = "ru")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sbert_russian_sentiment_rureviews_pipeline", lang = "ru")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sbert_russian_sentiment_rureviews_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ru|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/sismetanin/sbert-ru-sentiment-rureviews
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sbert_russian_sentiment_rureviews_ru.md b/docs/_posts/ahmedlone127/2024-09-08-sbert_russian_sentiment_rureviews_ru.md
new file mode 100644
index 00000000000000..34005385831370
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sbert_russian_sentiment_rureviews_ru.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Russian sbert_russian_sentiment_rureviews BertForSequenceClassification from sismetanin
+author: John Snow Labs
+name: sbert_russian_sentiment_rureviews
+date: 2024-09-08
+tags: [ru, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: ru
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sbert_russian_sentiment_rureviews` is a Russian model originally trained by sismetanin.
+
+{:.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/sbert_russian_sentiment_rureviews_ru_5.5.0_3.0_1725819414080.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sbert_russian_sentiment_rureviews_ru_5.5.0_3.0_1725819414080.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("sbert_russian_sentiment_rureviews","ru") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("sbert_russian_sentiment_rureviews", "ru")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sbert_russian_sentiment_rureviews|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|ru|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/sismetanin/sbert-ru-sentiment-rureviews
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-scenario_tcr_data_cardiffnlp_tweet_sentiment_multilingual_all_d_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-08-scenario_tcr_data_cardiffnlp_tweet_sentiment_multilingual_all_d_pipeline_xx.md
new file mode 100644
index 00000000000000..5f6773787703f4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-scenario_tcr_data_cardiffnlp_tweet_sentiment_multilingual_all_d_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual scenario_tcr_data_cardiffnlp_tweet_sentiment_multilingual_all_d_pipeline pipeline XlmRoBertaForSequenceClassification from haryoaw
+author: John Snow Labs
+name: scenario_tcr_data_cardiffnlp_tweet_sentiment_multilingual_all_d_pipeline
+date: 2024-09-08
+tags: [xx, open_source, pipeline, onnx]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scenario_tcr_data_cardiffnlp_tweet_sentiment_multilingual_all_d_pipeline` is a Multilingual model originally trained by haryoaw.
+
+{:.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/scenario_tcr_data_cardiffnlp_tweet_sentiment_multilingual_all_d_pipeline_xx_5.5.0_3.0_1725800281180.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scenario_tcr_data_cardiffnlp_tweet_sentiment_multilingual_all_d_pipeline_xx_5.5.0_3.0_1725800281180.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
+
+pipeline = PretrainedPipeline("scenario_tcr_data_cardiffnlp_tweet_sentiment_multilingual_all_d_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("scenario_tcr_data_cardiffnlp_tweet_sentiment_multilingual_all_d_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|scenario_tcr_data_cardiffnlp_tweet_sentiment_multilingual_all_d_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|836.5 MB|
+
+## References
+
+https://huggingface.co/haryoaw/scenario-TCR_data-cardiffnlp_tweet_sentiment_multilingual_all_d
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-schemeclassifier_eng_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-schemeclassifier_eng_pipeline_en.md
new file mode 100644
index 00000000000000..a5e8dbcc3680dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-schemeclassifier_eng_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English schemeclassifier_eng_pipeline pipeline RoBertaForSequenceClassification from raruidol
+author: John Snow Labs
+name: schemeclassifier_eng_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`schemeclassifier_eng_pipeline` is a English model originally trained by raruidol.
+
+{:.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/schemeclassifier_eng_pipeline_en_5.5.0_3.0_1725830903200.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/schemeclassifier_eng_pipeline_en_5.5.0_3.0_1725830903200.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
+
+pipeline = PretrainedPipeline("schemeclassifier_eng_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("schemeclassifier_eng_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|schemeclassifier_eng_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/raruidol/SchemeClassifier-ENG
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-self_harm_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-self_harm_bert_pipeline_en.md
new file mode 100644
index 00000000000000..76d8b08ea01650
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-self_harm_bert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English self_harm_bert_pipeline pipeline BertForSequenceClassification from dkuzmenko
+author: John Snow Labs
+name: self_harm_bert_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`self_harm_bert_pipeline` is a English model originally trained by dkuzmenko.
+
+{:.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/self_harm_bert_pipeline_en_5.5.0_3.0_1725825837835.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/self_harm_bert_pipeline_en_5.5.0_3.0_1725825837835.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
+
+pipeline = PretrainedPipeline("self_harm_bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("self_harm_bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|self_harm_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|627.8 MB|
+
+## References
+
+https://huggingface.co/dkuzmenko/self-harm-bert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-semanlink_all_mpnet_base_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-semanlink_all_mpnet_base_v2_pipeline_en.md
new file mode 100644
index 00000000000000..70f229a2054d26
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-semanlink_all_mpnet_base_v2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English semanlink_all_mpnet_base_v2_pipeline pipeline MPNetEmbeddings from raphaelsty
+author: John Snow Labs
+name: semanlink_all_mpnet_base_v2_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`semanlink_all_mpnet_base_v2_pipeline` is a English model originally trained by raphaelsty.
+
+{:.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/semanlink_all_mpnet_base_v2_pipeline_en_5.5.0_3.0_1725769768802.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/semanlink_all_mpnet_base_v2_pipeline_en_5.5.0_3.0_1725769768802.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
+
+pipeline = PretrainedPipeline("semanlink_all_mpnet_base_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("semanlink_all_mpnet_base_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|semanlink_all_mpnet_base_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.0 MB|
+
+## References
+
+https://huggingface.co/raphaelsty/semanlink_all_mpnet_base_v2
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_afro_xlmr_base_finetuned_kintweetsb_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_afro_xlmr_base_finetuned_kintweetsb_pipeline_en.md
new file mode 100644
index 00000000000000..9d7eaba0ac4b99
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_afro_xlmr_base_finetuned_kintweetsb_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_afro_xlmr_base_finetuned_kintweetsb_pipeline pipeline XlmRoBertaSentenceEmbeddings from RogerB
+author: John Snow Labs
+name: sent_afro_xlmr_base_finetuned_kintweetsb_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_afro_xlmr_base_finetuned_kintweetsb_pipeline` is a English model originally trained by RogerB.
+
+{:.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/sent_afro_xlmr_base_finetuned_kintweetsb_pipeline_en_5.5.0_3.0_1725759874807.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_afro_xlmr_base_finetuned_kintweetsb_pipeline_en_5.5.0_3.0_1725759874807.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
+
+pipeline = PretrainedPipeline("sent_afro_xlmr_base_finetuned_kintweetsb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_afro_xlmr_base_finetuned_kintweetsb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_afro_xlmr_base_finetuned_kintweetsb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/RogerB/afro-xlmr-base-finetuned-kintweetsB
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_alclam_base_v2_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_alclam_base_v2_en.md
new file mode 100644
index 00000000000000..eca92537881969
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_alclam_base_v2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_alclam_base_v2 BertSentenceEmbeddings from rahbi
+author: John Snow Labs
+name: sent_alclam_base_v2
+date: 2024-09-08
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_alclam_base_v2` is a English model originally trained by rahbi.
+
+{:.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/sent_alclam_base_v2_en_5.5.0_3.0_1725809677005.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_alclam_base_v2_en_5.5.0_3.0_1725809677005.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_alclam_base_v2","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_alclam_base_v2","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_alclam_base_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|607.1 MB|
+
+## References
+
+https://huggingface.co/rahbi/alclam-base-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_astrobert_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_astrobert_en.md
new file mode 100644
index 00000000000000..e24bff0af042a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_astrobert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_astrobert BertSentenceEmbeddings from adsabs
+author: John Snow Labs
+name: sent_astrobert
+date: 2024-09-08
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_astrobert` is a English model originally trained by adsabs.
+
+{:.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/sent_astrobert_en_5.5.0_3.0_1725809727338.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_astrobert_en_5.5.0_3.0_1725809727338.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_astrobert","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_astrobert","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_astrobert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|405.7 MB|
+
+## References
+
+https://huggingface.co/adsabs/astroBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_astrobert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_astrobert_pipeline_en.md
new file mode 100644
index 00000000000000..9eb33a9f6dc27b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_astrobert_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_astrobert_pipeline pipeline BertSentenceEmbeddings from adsabs
+author: John Snow Labs
+name: sent_astrobert_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_astrobert_pipeline` is a English model originally trained by adsabs.
+
+{:.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/sent_astrobert_pipeline_en_5.5.0_3.0_1725809747701.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_astrobert_pipeline_en_5.5.0_3.0_1725809747701.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
+
+pipeline = PretrainedPipeline("sent_astrobert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_astrobert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_astrobert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.2 MB|
+
+## References
+
+https://huggingface.co/adsabs/astroBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_bert_base_arabic_camelbert_msa_sixteenth_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-08-sent_bert_base_arabic_camelbert_msa_sixteenth_pipeline_ar.md
new file mode 100644
index 00000000000000..db7a632646e7eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_bert_base_arabic_camelbert_msa_sixteenth_pipeline_ar.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Arabic sent_bert_base_arabic_camelbert_msa_sixteenth_pipeline pipeline BertSentenceEmbeddings from CAMeL-Lab
+author: John Snow Labs
+name: sent_bert_base_arabic_camelbert_msa_sixteenth_pipeline
+date: 2024-09-08
+tags: [ar, open_source, pipeline, onnx]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_arabic_camelbert_msa_sixteenth_pipeline` is a Arabic model originally trained by CAMeL-Lab.
+
+{:.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/sent_bert_base_arabic_camelbert_msa_sixteenth_pipeline_ar_5.5.0_3.0_1725790859566.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_arabic_camelbert_msa_sixteenth_pipeline_ar_5.5.0_3.0_1725790859566.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
+
+pipeline = PretrainedPipeline("sent_bert_base_arabic_camelbert_msa_sixteenth_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_arabic_camelbert_msa_sixteenth_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_arabic_camelbert_msa_sixteenth_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-msa-sixteenth
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_bert_base_italian_uncased_dbmdz_it.md b/docs/_posts/ahmedlone127/2024-09-08-sent_bert_base_italian_uncased_dbmdz_it.md
new file mode 100644
index 00000000000000..008fc789efdf52
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_bert_base_italian_uncased_dbmdz_it.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Italian sent_bert_base_italian_uncased_dbmdz BertSentenceEmbeddings from dbmdz
+author: John Snow Labs
+name: sent_bert_base_italian_uncased_dbmdz
+date: 2024-09-08
+tags: [it, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: it
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_italian_uncased_dbmdz` is a Italian model originally trained by dbmdz.
+
+{:.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/sent_bert_base_italian_uncased_dbmdz_it_5.5.0_3.0_1725809897011.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_italian_uncased_dbmdz_it_5.5.0_3.0_1725809897011.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_italian_uncased_dbmdz","it") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_italian_uncased_dbmdz","it") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_italian_uncased_dbmdz|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|it|
+|Size:|409.7 MB|
+
+## References
+
+https://huggingface.co/dbmdz/bert-base-italian-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_bert_base_italian_uncased_dbmdz_pipeline_it.md b/docs/_posts/ahmedlone127/2024-09-08-sent_bert_base_italian_uncased_dbmdz_pipeline_it.md
new file mode 100644
index 00000000000000..87e33e64f18f85
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_bert_base_italian_uncased_dbmdz_pipeline_it.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Italian sent_bert_base_italian_uncased_dbmdz_pipeline pipeline BertSentenceEmbeddings from dbmdz
+author: John Snow Labs
+name: sent_bert_base_italian_uncased_dbmdz_pipeline
+date: 2024-09-08
+tags: [it, open_source, pipeline, onnx]
+task: Embeddings
+language: it
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_italian_uncased_dbmdz_pipeline` is a Italian model originally trained by dbmdz.
+
+{:.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/sent_bert_base_italian_uncased_dbmdz_pipeline_it_5.5.0_3.0_1725809918276.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_italian_uncased_dbmdz_pipeline_it_5.5.0_3.0_1725809918276.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
+
+pipeline = PretrainedPipeline("sent_bert_base_italian_uncased_dbmdz_pipeline", lang = "it")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_italian_uncased_dbmdz_pipeline", lang = "it")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_italian_uncased_dbmdz_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|it|
+|Size:|410.3 MB|
+
+## References
+
+https://huggingface.co/dbmdz/bert-base-italian-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_bert_base_uncased_google_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_bert_base_uncased_google_bert_pipeline_en.md
new file mode 100644
index 00000000000000..ba2c174ba58d87
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_bert_base_uncased_google_bert_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_base_uncased_google_bert_pipeline pipeline BertSentenceEmbeddings from google-bert
+author: John Snow Labs
+name: sent_bert_base_uncased_google_bert_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_google_bert_pipeline` is a English model originally trained by google-bert.
+
+{:.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/sent_bert_base_uncased_google_bert_pipeline_en_5.5.0_3.0_1725790862036.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_google_bert_pipeline_en_5.5.0_3.0_1725790862036.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
+
+pipeline = PretrainedPipeline("sent_bert_base_uncased_google_bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_base_uncased_google_bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_base_uncased_google_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/google-bert/bert-base-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_bert_mini_arabic_ar.md b/docs/_posts/ahmedlone127/2024-09-08-sent_bert_mini_arabic_ar.md
new file mode 100644
index 00000000000000..4580ff00f8913e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_bert_mini_arabic_ar.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Arabic sent_bert_mini_arabic BertSentenceEmbeddings from asafaya
+author: John Snow Labs
+name: sent_bert_mini_arabic
+date: 2024-09-08
+tags: [ar, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_mini_arabic` is a Arabic model originally trained by asafaya.
+
+{:.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/sent_bert_mini_arabic_ar_5.5.0_3.0_1725810315980.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_mini_arabic_ar_5.5.0_3.0_1725810315980.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_mini_arabic","ar") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_mini_arabic","ar") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_mini_arabic|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|ar|
+|Size:|43.3 MB|
+
+## References
+
+https://huggingface.co/asafaya/bert-mini-arabic
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_bert_mini_arabic_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-08-sent_bert_mini_arabic_pipeline_ar.md
new file mode 100644
index 00000000000000..62be3609c19ba4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_bert_mini_arabic_pipeline_ar.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Arabic sent_bert_mini_arabic_pipeline pipeline BertSentenceEmbeddings from asafaya
+author: John Snow Labs
+name: sent_bert_mini_arabic_pipeline
+date: 2024-09-08
+tags: [ar, open_source, pipeline, onnx]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_mini_arabic_pipeline` is a Arabic model originally trained by asafaya.
+
+{:.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/sent_bert_mini_arabic_pipeline_ar_5.5.0_3.0_1725810318445.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_mini_arabic_pipeline_ar_5.5.0_3.0_1725810318445.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
+
+pipeline = PretrainedPipeline("sent_bert_mini_arabic_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_mini_arabic_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_mini_arabic_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|43.9 MB|
+
+## References
+
+https://huggingface.co/asafaya/bert-mini-arabic
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_bert_persian_farsi_base_uncased_fa.md b/docs/_posts/ahmedlone127/2024-09-08-sent_bert_persian_farsi_base_uncased_fa.md
new file mode 100644
index 00000000000000..1b3278a800c5db
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_bert_persian_farsi_base_uncased_fa.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Persian sent_bert_persian_farsi_base_uncased BertSentenceEmbeddings from HooshvareLab
+author: John Snow Labs
+name: sent_bert_persian_farsi_base_uncased
+date: 2024-09-08
+tags: [fa, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: fa
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_persian_farsi_base_uncased` is a Persian model originally trained by HooshvareLab.
+
+{:.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/sent_bert_persian_farsi_base_uncased_fa_5.5.0_3.0_1725810222341.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_persian_farsi_base_uncased_fa_5.5.0_3.0_1725810222341.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_persian_farsi_base_uncased","fa") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_persian_farsi_base_uncased","fa") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_persian_farsi_base_uncased|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|fa|
+|Size:|606.5 MB|
+
+## References
+
+https://huggingface.co/HooshvareLab/bert-fa-base-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_bert_persian_farsi_base_uncased_pipeline_fa.md b/docs/_posts/ahmedlone127/2024-09-08-sent_bert_persian_farsi_base_uncased_pipeline_fa.md
new file mode 100644
index 00000000000000..ed6940701619c9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_bert_persian_farsi_base_uncased_pipeline_fa.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Persian sent_bert_persian_farsi_base_uncased_pipeline pipeline BertSentenceEmbeddings from HooshvareLab
+author: John Snow Labs
+name: sent_bert_persian_farsi_base_uncased_pipeline
+date: 2024-09-08
+tags: [fa, open_source, pipeline, onnx]
+task: Embeddings
+language: fa
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_persian_farsi_base_uncased_pipeline` is a Persian model originally trained by HooshvareLab.
+
+{:.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/sent_bert_persian_farsi_base_uncased_pipeline_fa_5.5.0_3.0_1725810253535.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_persian_farsi_base_uncased_pipeline_fa_5.5.0_3.0_1725810253535.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
+
+pipeline = PretrainedPipeline("sent_bert_persian_farsi_base_uncased_pipeline", lang = "fa")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_persian_farsi_base_uncased_pipeline", lang = "fa")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_persian_farsi_base_uncased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|fa|
+|Size:|607.1 MB|
+
+## References
+
+https://huggingface.co/HooshvareLab/bert-fa-base-uncased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_bert_web_bulgarian_cased_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_bert_web_bulgarian_cased_en.md
new file mode 100644
index 00000000000000..7432ef11de1fe2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_bert_web_bulgarian_cased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bert_web_bulgarian_cased BertSentenceEmbeddings from usmiva
+author: John Snow Labs
+name: sent_bert_web_bulgarian_cased
+date: 2024-09-08
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_web_bulgarian_cased` is a English model originally trained by usmiva.
+
+{:.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/sent_bert_web_bulgarian_cased_en_5.5.0_3.0_1725791343467.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_web_bulgarian_cased_en_5.5.0_3.0_1725791343467.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bert_web_bulgarian_cased","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_web_bulgarian_cased","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_web_bulgarian_cased|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|408.4 MB|
+
+## References
+
+https://huggingface.co/usmiva/bert-web-bg-cased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_bert_web_bulgarian_cased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_bert_web_bulgarian_cased_pipeline_en.md
new file mode 100644
index 00000000000000..6dc87653f14d33
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_bert_web_bulgarian_cased_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bert_web_bulgarian_cased_pipeline pipeline BertSentenceEmbeddings from usmiva
+author: John Snow Labs
+name: sent_bert_web_bulgarian_cased_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_web_bulgarian_cased_pipeline` is a English model originally trained by usmiva.
+
+{:.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/sent_bert_web_bulgarian_cased_pipeline_en_5.5.0_3.0_1725791361843.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_web_bulgarian_cased_pipeline_en_5.5.0_3.0_1725791361843.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
+
+pipeline = PretrainedPipeline("sent_bert_web_bulgarian_cased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bert_web_bulgarian_cased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bert_web_bulgarian_cased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.9 MB|
+
+## References
+
+https://huggingface.co/usmiva/bert-web-bg-cased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_biobert_base_cased_v1_2_dmis_lab_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_biobert_base_cased_v1_2_dmis_lab_pipeline_en.md
new file mode 100644
index 00000000000000..769a66ac5725c5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_biobert_base_cased_v1_2_dmis_lab_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_biobert_base_cased_v1_2_dmis_lab_pipeline pipeline BertSentenceEmbeddings from dmis-lab
+author: John Snow Labs
+name: sent_biobert_base_cased_v1_2_dmis_lab_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_biobert_base_cased_v1_2_dmis_lab_pipeline` is a English model originally trained by dmis-lab.
+
+{:.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/sent_biobert_base_cased_v1_2_dmis_lab_pipeline_en_5.5.0_3.0_1725790987523.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_biobert_base_cased_v1_2_dmis_lab_pipeline_en_5.5.0_3.0_1725790987523.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
+
+pipeline = PretrainedPipeline("sent_biobert_base_cased_v1_2_dmis_lab_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_biobert_base_cased_v1_2_dmis_lab_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_biobert_base_cased_v1_2_dmis_lab_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|404.2 MB|
+
+## References
+
+https://huggingface.co/dmis-lab/biobert-base-cased-v1.2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_bioformer_8l_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_bioformer_8l_en.md
new file mode 100644
index 00000000000000..eacff76e21cff8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_bioformer_8l_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_bioformer_8l BertSentenceEmbeddings from bioformers
+author: John Snow Labs
+name: sent_bioformer_8l
+date: 2024-09-08
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bioformer_8l` is a English model originally trained by bioformers.
+
+{:.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/sent_bioformer_8l_en_5.5.0_3.0_1725791274510.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bioformer_8l_en_5.5.0_3.0_1725791274510.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_bioformer_8l","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_bioformer_8l","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bioformer_8l|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|158.5 MB|
+
+## References
+
+https://huggingface.co/bioformers/bioformer-8L
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_bioformer_8l_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_bioformer_8l_pipeline_en.md
new file mode 100644
index 00000000000000..7a531fea573b30
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_bioformer_8l_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_bioformer_8l_pipeline pipeline BertSentenceEmbeddings from bioformers
+author: John Snow Labs
+name: sent_bioformer_8l_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bioformer_8l_pipeline` is a English model originally trained by bioformers.
+
+{:.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/sent_bioformer_8l_pipeline_en_5.5.0_3.0_1725791283588.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bioformer_8l_pipeline_en_5.5.0_3.0_1725791283588.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
+
+pipeline = PretrainedPipeline("sent_bioformer_8l_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_bioformer_8l_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_bioformer_8l_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|159.1 MB|
+
+## References
+
+https://huggingface.co/bioformers/bioformer-8L
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_compact_biobert_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_compact_biobert_en.md
new file mode 100644
index 00000000000000..294ae4890ae5ad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_compact_biobert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_compact_biobert BertSentenceEmbeddings from nlpie
+author: John Snow Labs
+name: sent_compact_biobert
+date: 2024-09-08
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_compact_biobert` is a English model originally trained by nlpie.
+
+{:.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/sent_compact_biobert_en_5.5.0_3.0_1725810468956.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_compact_biobert_en_5.5.0_3.0_1725810468956.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_compact_biobert","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_compact_biobert","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_compact_biobert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|244.4 MB|
+
+## References
+
+https://huggingface.co/nlpie/compact-biobert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_cysecbert_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_cysecbert_en.md
new file mode 100644
index 00000000000000..2c05ea555bebb7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_cysecbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_cysecbert BertSentenceEmbeddings from markusbayer
+author: John Snow Labs
+name: sent_cysecbert
+date: 2024-09-08
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_cysecbert` is a English model originally trained by markusbayer.
+
+{:.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/sent_cysecbert_en_5.5.0_3.0_1725810081787.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_cysecbert_en_5.5.0_3.0_1725810081787.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_cysecbert","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_cysecbert","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_cysecbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/markusbayer/CySecBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_cysecbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_cysecbert_pipeline_en.md
new file mode 100644
index 00000000000000..ef658f103c0146
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_cysecbert_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_cysecbert_pipeline pipeline BertSentenceEmbeddings from markusbayer
+author: John Snow Labs
+name: sent_cysecbert_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_cysecbert_pipeline` is a English model originally trained by markusbayer.
+
+{:.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/sent_cysecbert_pipeline_en_5.5.0_3.0_1725810102365.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_cysecbert_pipeline_en_5.5.0_3.0_1725810102365.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
+
+pipeline = PretrainedPipeline("sent_cysecbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_cysecbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_cysecbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.6 MB|
+
+## References
+
+https://huggingface.co/markusbayer/CySecBERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_econobert_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_econobert_en.md
new file mode 100644
index 00000000000000..38f7494854345c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_econobert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_econobert BertSentenceEmbeddings from samchain
+author: John Snow Labs
+name: sent_econobert
+date: 2024-09-08
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_econobert` is a English model originally trained by samchain.
+
+{:.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/sent_econobert_en_5.5.0_3.0_1725809786657.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_econobert_en_5.5.0_3.0_1725809786657.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_econobert","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_econobert","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_econobert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/samchain/EconoBert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_econobert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_econobert_pipeline_en.md
new file mode 100644
index 00000000000000..e988338b3fa2e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_econobert_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_econobert_pipeline pipeline BertSentenceEmbeddings from samchain
+author: John Snow Labs
+name: sent_econobert_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_econobert_pipeline` is a English model originally trained by samchain.
+
+{:.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/sent_econobert_pipeline_en_5.5.0_3.0_1725809807004.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_econobert_pipeline_en_5.5.0_3.0_1725809807004.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
+
+pipeline = PretrainedPipeline("sent_econobert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_econobert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_econobert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.7 MB|
+
+## References
+
+https://huggingface.co/samchain/EconoBert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_english_japanese_xlm_5_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_english_japanese_xlm_5_en.md
new file mode 100644
index 00000000000000..070afbe0afa7e0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_english_japanese_xlm_5_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_english_japanese_xlm_5 XlmRoBertaSentenceEmbeddings from Sotaro0124
+author: John Snow Labs
+name: sent_english_japanese_xlm_5
+date: 2024-09-08
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+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.`sent_english_japanese_xlm_5` is a English model originally trained by Sotaro0124.
+
+{:.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/sent_english_japanese_xlm_5_en_5.5.0_3.0_1725796882958.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_english_japanese_xlm_5_en_5.5.0_3.0_1725796882958.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_english_japanese_xlm_5","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_english_japanese_xlm_5","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_english_japanese_xlm_5|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Sotaro0124/en_ja_xlm_5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_english_japanese_xlm_5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_english_japanese_xlm_5_pipeline_en.md
new file mode 100644
index 00000000000000..00e70e96871c1f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_english_japanese_xlm_5_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_english_japanese_xlm_5_pipeline pipeline XlmRoBertaSentenceEmbeddings from Sotaro0124
+author: John Snow Labs
+name: sent_english_japanese_xlm_5_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_english_japanese_xlm_5_pipeline` is a English model originally trained by Sotaro0124.
+
+{:.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/sent_english_japanese_xlm_5_pipeline_en_5.5.0_3.0_1725796933044.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_english_japanese_xlm_5_pipeline_en_5.5.0_3.0_1725796933044.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
+
+pipeline = PretrainedPipeline("sent_english_japanese_xlm_5_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_english_japanese_xlm_5_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_english_japanese_xlm_5_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Sotaro0124/en_ja_xlm_5
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_fernet_c5_cs.md b/docs/_posts/ahmedlone127/2024-09-08-sent_fernet_c5_cs.md
new file mode 100644
index 00000000000000..dbcfbde4036d30
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_fernet_c5_cs.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Czech sent_fernet_c5 BertSentenceEmbeddings from fav-kky
+author: John Snow Labs
+name: sent_fernet_c5
+date: 2024-09-08
+tags: [cs, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: cs
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_fernet_c5` is a Czech model originally trained by fav-kky.
+
+{:.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/sent_fernet_c5_cs_5.5.0_3.0_1725810333301.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_fernet_c5_cs_5.5.0_3.0_1725810333301.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_fernet_c5","cs") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_fernet_c5","cs") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_fernet_c5|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|cs|
+|Size:|609.5 MB|
+
+## References
+
+https://huggingface.co/fav-kky/FERNET-C5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_flang_bert_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_flang_bert_en.md
new file mode 100644
index 00000000000000..ad935662abda8a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_flang_bert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_flang_bert BertSentenceEmbeddings from SALT-NLP
+author: John Snow Labs
+name: sent_flang_bert
+date: 2024-09-08
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_flang_bert` is a English model originally trained by SALT-NLP.
+
+{:.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/sent_flang_bert_en_5.5.0_3.0_1725790808560.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_flang_bert_en_5.5.0_3.0_1725790808560.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_flang_bert","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_flang_bert","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_flang_bert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/SALT-NLP/FLANG-BERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_gujarati_in_devanagari_xlm_r_base_gu.md b/docs/_posts/ahmedlone127/2024-09-08-sent_gujarati_in_devanagari_xlm_r_base_gu.md
new file mode 100644
index 00000000000000..bc68520391bdd1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_gujarati_in_devanagari_xlm_r_base_gu.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Gujarati sent_gujarati_in_devanagari_xlm_r_base XlmRoBertaSentenceEmbeddings from ashwani-tanwar
+author: John Snow Labs
+name: sent_gujarati_in_devanagari_xlm_r_base
+date: 2024-09-08
+tags: [gu, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: gu
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+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.`sent_gujarati_in_devanagari_xlm_r_base` is a Gujarati model originally trained by ashwani-tanwar.
+
+{:.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/sent_gujarati_in_devanagari_xlm_r_base_gu_5.5.0_3.0_1725797452726.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_gujarati_in_devanagari_xlm_r_base_gu_5.5.0_3.0_1725797452726.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_gujarati_in_devanagari_xlm_r_base","gu") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_gujarati_in_devanagari_xlm_r_base","gu") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_gujarati_in_devanagari_xlm_r_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|gu|
+|Size:|652.8 MB|
+
+## References
+
+https://huggingface.co/ashwani-tanwar/Gujarati-in-Devanagari-XLM-R-Base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_gujarati_in_devanagari_xlm_r_base_pipeline_gu.md b/docs/_posts/ahmedlone127/2024-09-08-sent_gujarati_in_devanagari_xlm_r_base_pipeline_gu.md
new file mode 100644
index 00000000000000..e9ccf571e8ebd7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_gujarati_in_devanagari_xlm_r_base_pipeline_gu.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Gujarati sent_gujarati_in_devanagari_xlm_r_base_pipeline pipeline XlmRoBertaSentenceEmbeddings from ashwani-tanwar
+author: John Snow Labs
+name: sent_gujarati_in_devanagari_xlm_r_base_pipeline
+date: 2024-09-08
+tags: [gu, open_source, pipeline, onnx]
+task: Embeddings
+language: gu
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_gujarati_in_devanagari_xlm_r_base_pipeline` is a Gujarati model originally trained by ashwani-tanwar.
+
+{:.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/sent_gujarati_in_devanagari_xlm_r_base_pipeline_gu_5.5.0_3.0_1725797631926.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_gujarati_in_devanagari_xlm_r_base_pipeline_gu_5.5.0_3.0_1725797631926.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
+
+pipeline = PretrainedPipeline("sent_gujarati_in_devanagari_xlm_r_base_pipeline", lang = "gu")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_gujarati_in_devanagari_xlm_r_base_pipeline", lang = "gu")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_gujarati_in_devanagari_xlm_r_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|gu|
+|Size:|653.3 MB|
+
+## References
+
+https://huggingface.co/ashwani-tanwar/Gujarati-in-Devanagari-XLM-R-Base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_hindi_bert_scratch_hi.md b/docs/_posts/ahmedlone127/2024-09-08-sent_hindi_bert_scratch_hi.md
new file mode 100644
index 00000000000000..4a790fa41d2699
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_hindi_bert_scratch_hi.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Hindi sent_hindi_bert_scratch BertSentenceEmbeddings from l3cube-pune
+author: John Snow Labs
+name: sent_hindi_bert_scratch
+date: 2024-09-08
+tags: [hi, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: hi
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_hindi_bert_scratch` is a Hindi model originally trained by l3cube-pune.
+
+{:.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/sent_hindi_bert_scratch_hi_5.5.0_3.0_1725790851047.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_hindi_bert_scratch_hi_5.5.0_3.0_1725790851047.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_hindi_bert_scratch","hi") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_hindi_bert_scratch","hi") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_hindi_bert_scratch|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|hi|
+|Size:|470.6 MB|
+
+## References
+
+https://huggingface.co/l3cube-pune/hindi-bert-scratch
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_hing_mbert_mixed_hi.md b/docs/_posts/ahmedlone127/2024-09-08-sent_hing_mbert_mixed_hi.md
new file mode 100644
index 00000000000000..72e861deedfb9e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_hing_mbert_mixed_hi.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Hindi sent_hing_mbert_mixed BertSentenceEmbeddings from l3cube-pune
+author: John Snow Labs
+name: sent_hing_mbert_mixed
+date: 2024-09-08
+tags: [hi, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: hi
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_hing_mbert_mixed` is a Hindi model originally trained by l3cube-pune.
+
+{:.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/sent_hing_mbert_mixed_hi_5.5.0_3.0_1725791396624.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_hing_mbert_mixed_hi_5.5.0_3.0_1725791396624.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_hing_mbert_mixed","hi") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_hing_mbert_mixed","hi") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_hing_mbert_mixed|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|hi|
+|Size:|664.9 MB|
+
+## References
+
+https://huggingface.co/l3cube-pune/hing-mbert-mixed
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_hing_mbert_mixed_pipeline_hi.md b/docs/_posts/ahmedlone127/2024-09-08-sent_hing_mbert_mixed_pipeline_hi.md
new file mode 100644
index 00000000000000..7c7198fd0952d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_hing_mbert_mixed_pipeline_hi.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Hindi sent_hing_mbert_mixed_pipeline pipeline BertSentenceEmbeddings from l3cube-pune
+author: John Snow Labs
+name: sent_hing_mbert_mixed_pipeline
+date: 2024-09-08
+tags: [hi, open_source, pipeline, onnx]
+task: Embeddings
+language: hi
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_hing_mbert_mixed_pipeline` is a Hindi model originally trained by l3cube-pune.
+
+{:.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/sent_hing_mbert_mixed_pipeline_hi_5.5.0_3.0_1725791428131.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_hing_mbert_mixed_pipeline_hi_5.5.0_3.0_1725791428131.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
+
+pipeline = PretrainedPipeline("sent_hing_mbert_mixed_pipeline", lang = "hi")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_hing_mbert_mixed_pipeline", lang = "hi")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_hing_mbert_mixed_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|hi|
+|Size:|665.5 MB|
+
+## References
+
+https://huggingface.co/l3cube-pune/hing-mbert-mixed
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_javabert_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_javabert_en.md
new file mode 100644
index 00000000000000..181a33246b7db4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_javabert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_javabert BertSentenceEmbeddings from CAUKiel
+author: John Snow Labs
+name: sent_javabert
+date: 2024-09-08
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_javabert` is a English model originally trained by CAUKiel.
+
+{:.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/sent_javabert_en_5.5.0_3.0_1725810161667.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_javabert_en_5.5.0_3.0_1725810161667.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_javabert","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_javabert","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_javabert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|408.2 MB|
+
+## References
+
+https://huggingface.co/CAUKiel/JavaBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_jobbert_base_cased_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_jobbert_base_cased_en.md
new file mode 100644
index 00000000000000..c74c44ff9d5b09
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_jobbert_base_cased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_jobbert_base_cased BertSentenceEmbeddings from jjzha
+author: John Snow Labs
+name: sent_jobbert_base_cased
+date: 2024-09-08
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_jobbert_base_cased` is a English model originally trained by jjzha.
+
+{:.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/sent_jobbert_base_cased_en_5.5.0_3.0_1725791481723.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_jobbert_base_cased_en_5.5.0_3.0_1725791481723.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_jobbert_base_cased","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_jobbert_base_cased","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_jobbert_base_cased|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|402.2 MB|
+
+## References
+
+https://huggingface.co/jjzha/jobbert-base-cased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_jobbert_base_cased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_jobbert_base_cased_pipeline_en.md
new file mode 100644
index 00000000000000..3de5c88db2c9ce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_jobbert_base_cased_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_jobbert_base_cased_pipeline pipeline BertSentenceEmbeddings from jjzha
+author: John Snow Labs
+name: sent_jobbert_base_cased_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_jobbert_base_cased_pipeline` is a English model originally trained by jjzha.
+
+{:.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/sent_jobbert_base_cased_pipeline_en_5.5.0_3.0_1725791499501.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_jobbert_base_cased_pipeline_en_5.5.0_3.0_1725791499501.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
+
+pipeline = PretrainedPipeline("sent_jobbert_base_cased_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_jobbert_base_cased_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_jobbert_base_cased_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|402.8 MB|
+
+## References
+
+https://huggingface.co/jjzha/jobbert-base-cased
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_legalbert_large_1_7m_1_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_legalbert_large_1_7m_1_en.md
new file mode 100644
index 00000000000000..90ccad61a3d2b8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_legalbert_large_1_7m_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_legalbert_large_1_7m_1 BertSentenceEmbeddings from pile-of-law
+author: John Snow Labs
+name: sent_legalbert_large_1_7m_1
+date: 2024-09-08
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_legalbert_large_1_7m_1` is a English model originally trained by pile-of-law.
+
+{:.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/sent_legalbert_large_1_7m_1_en_5.5.0_3.0_1725809839825.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_legalbert_large_1_7m_1_en_5.5.0_3.0_1725809839825.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_legalbert_large_1_7m_1","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_legalbert_large_1_7m_1","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_legalbert_large_1_7m_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|643.5 MB|
+
+## References
+
+https://huggingface.co/pile-of-law/legalbert-large-1.7M-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_legalbert_large_1_7m_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_legalbert_large_1_7m_1_pipeline_en.md
new file mode 100644
index 00000000000000..5530915b9c2eeb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_legalbert_large_1_7m_1_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_legalbert_large_1_7m_1_pipeline pipeline BertSentenceEmbeddings from pile-of-law
+author: John Snow Labs
+name: sent_legalbert_large_1_7m_1_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_legalbert_large_1_7m_1_pipeline` is a English model originally trained by pile-of-law.
+
+{:.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/sent_legalbert_large_1_7m_1_pipeline_en_5.5.0_3.0_1725810055951.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_legalbert_large_1_7m_1_pipeline_en_5.5.0_3.0_1725810055951.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
+
+pipeline = PretrainedPipeline("sent_legalbert_large_1_7m_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_legalbert_large_1_7m_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_legalbert_large_1_7m_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|644.1 MB|
+
+## References
+
+https://huggingface.co/pile-of-law/legalbert-large-1.7M-1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_marathi_bert_v2_mr.md b/docs/_posts/ahmedlone127/2024-09-08-sent_marathi_bert_v2_mr.md
new file mode 100644
index 00000000000000..5877fbf4beb471
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_marathi_bert_v2_mr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Marathi sent_marathi_bert_v2 BertSentenceEmbeddings from l3cube-pune
+author: John Snow Labs
+name: sent_marathi_bert_v2
+date: 2024-09-08
+tags: [mr, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: mr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_marathi_bert_v2` is a Marathi model originally trained by l3cube-pune.
+
+{:.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/sent_marathi_bert_v2_mr_5.5.0_3.0_1725809638993.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_marathi_bert_v2_mr_5.5.0_3.0_1725809638993.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_marathi_bert_v2","mr") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_marathi_bert_v2","mr") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_marathi_bert_v2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|mr|
+|Size:|890.6 MB|
+
+## References
+
+https://huggingface.co/l3cube-pune/marathi-bert-v2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_mbertu_mt.md b/docs/_posts/ahmedlone127/2024-09-08-sent_mbertu_mt.md
new file mode 100644
index 00000000000000..d8254ce57c4f48
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_mbertu_mt.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Maltese sent_mbertu BertSentenceEmbeddings from MLRS
+author: John Snow Labs
+name: sent_mbertu
+date: 2024-09-08
+tags: [mt, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: mt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mbertu` is a Maltese model originally trained by MLRS.
+
+{:.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/sent_mbertu_mt_5.5.0_3.0_1725790684391.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mbertu_mt_5.5.0_3.0_1725790684391.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_mbertu","mt") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_mbertu","mt") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_mbertu|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|mt|
+|Size:|664.6 MB|
+
+## References
+
+https://huggingface.co/MLRS/mBERTu
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_memo_model_2500_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_memo_model_2500_en.md
new file mode 100644
index 00000000000000..43f630e3840a54
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_memo_model_2500_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_memo_model_2500 XlmRoBertaSentenceEmbeddings from yemen2016
+author: John Snow Labs
+name: sent_memo_model_2500
+date: 2024-09-08
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+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.`sent_memo_model_2500` is a English model originally trained by yemen2016.
+
+{:.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/sent_memo_model_2500_en_5.5.0_3.0_1725759509501.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_memo_model_2500_en_5.5.0_3.0_1725759509501.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_memo_model_2500","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_memo_model_2500","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_memo_model_2500|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/yemen2016/memo_model_2500
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_multi_dialect_bert_base_arabic_ar.md b/docs/_posts/ahmedlone127/2024-09-08-sent_multi_dialect_bert_base_arabic_ar.md
new file mode 100644
index 00000000000000..9e158202664c77
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_multi_dialect_bert_base_arabic_ar.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Arabic sent_multi_dialect_bert_base_arabic BertSentenceEmbeddings from bashar-talafha
+author: John Snow Labs
+name: sent_multi_dialect_bert_base_arabic
+date: 2024-09-08
+tags: [ar, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_multi_dialect_bert_base_arabic` is a Arabic model originally trained by bashar-talafha.
+
+{:.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/sent_multi_dialect_bert_base_arabic_ar_5.5.0_3.0_1725810343656.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_multi_dialect_bert_base_arabic_ar_5.5.0_3.0_1725810343656.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_multi_dialect_bert_base_arabic","ar") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_multi_dialect_bert_base_arabic","ar") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_multi_dialect_bert_base_arabic|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|ar|
+|Size:|411.5 MB|
+
+## References
+
+https://huggingface.co/bashar-talafha/multi-dialect-bert-base-arabic
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_norwegian_bokml_bert_large_no.md b/docs/_posts/ahmedlone127/2024-09-08-sent_norwegian_bokml_bert_large_no.md
new file mode 100644
index 00000000000000..9a19ec81975f2e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_norwegian_bokml_bert_large_no.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Norwegian sent_norwegian_bokml_bert_large BertSentenceEmbeddings from NbAiLab
+author: John Snow Labs
+name: sent_norwegian_bokml_bert_large
+date: 2024-09-08
+tags: ["no", open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: "no"
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_norwegian_bokml_bert_large` is a Norwegian model originally trained by NbAiLab.
+
+{:.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/sent_norwegian_bokml_bert_large_no_5.5.0_3.0_1725810133403.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_norwegian_bokml_bert_large_no_5.5.0_3.0_1725810133403.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_norwegian_bokml_bert_large","no") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_norwegian_bokml_bert_large","no") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_norwegian_bokml_bert_large|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|no|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/NbAiLab/nb-bert-large
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_norwegian_bokml_roberta_base_scandi_1e4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_norwegian_bokml_roberta_base_scandi_1e4_pipeline_en.md
new file mode 100644
index 00000000000000..52f8c0d5e4a594
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_norwegian_bokml_roberta_base_scandi_1e4_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_norwegian_bokml_roberta_base_scandi_1e4_pipeline pipeline XlmRoBertaSentenceEmbeddings from NbAiLab
+author: John Snow Labs
+name: sent_norwegian_bokml_roberta_base_scandi_1e4_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_norwegian_bokml_roberta_base_scandi_1e4_pipeline` is a English model originally trained by NbAiLab.
+
+{:.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/sent_norwegian_bokml_roberta_base_scandi_1e4_pipeline_en_5.5.0_3.0_1725759475464.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_norwegian_bokml_roberta_base_scandi_1e4_pipeline_en_5.5.0_3.0_1725759475464.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
+
+pipeline = PretrainedPipeline("sent_norwegian_bokml_roberta_base_scandi_1e4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_norwegian_bokml_roberta_base_scandi_1e4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_norwegian_bokml_roberta_base_scandi_1e4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/NbAiLab/nb-roberta-base-scandi-1e4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_nusabert_base_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_nusabert_base_en.md
new file mode 100644
index 00000000000000..e6e18138cfcd8d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_nusabert_base_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_nusabert_base BertSentenceEmbeddings from LazarusNLP
+author: John Snow Labs
+name: sent_nusabert_base
+date: 2024-09-08
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_nusabert_base` is a English model originally trained by LazarusNLP.
+
+{:.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/sent_nusabert_base_en_5.5.0_3.0_1725810179008.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_nusabert_base_en_5.5.0_3.0_1725810179008.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_nusabert_base","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_nusabert_base","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_nusabert_base|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|412.4 MB|
+
+## References
+
+https://huggingface.co/LazarusNLP/NusaBERT-base
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_nusabert_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_nusabert_base_pipeline_en.md
new file mode 100644
index 00000000000000..d9c8b6319eae98
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_nusabert_base_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_nusabert_base_pipeline pipeline BertSentenceEmbeddings from LazarusNLP
+author: John Snow Labs
+name: sent_nusabert_base_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_nusabert_base_pipeline` is a English model originally trained by LazarusNLP.
+
+{:.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/sent_nusabert_base_pipeline_en_5.5.0_3.0_1725810201014.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_nusabert_base_pipeline_en_5.5.0_3.0_1725810201014.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
+
+pipeline = PretrainedPipeline("sent_nusabert_base_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_nusabert_base_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_nusabert_base_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|412.9 MB|
+
+## References
+
+https://huggingface.co/LazarusNLP/NusaBERT-base
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_pretrained_xlm_portuguese_e8_all_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_pretrained_xlm_portuguese_e8_all_en.md
new file mode 100644
index 00000000000000..c3696cc5f3eb21
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_pretrained_xlm_portuguese_e8_all_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_pretrained_xlm_portuguese_e8_all XlmRoBertaSentenceEmbeddings from harish
+author: John Snow Labs
+name: sent_pretrained_xlm_portuguese_e8_all
+date: 2024-09-08
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+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.`sent_pretrained_xlm_portuguese_e8_all` is a English model originally trained by harish.
+
+{:.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/sent_pretrained_xlm_portuguese_e8_all_en_5.5.0_3.0_1725813439764.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_pretrained_xlm_portuguese_e8_all_en_5.5.0_3.0_1725813439764.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_pretrained_xlm_portuguese_e8_all","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_pretrained_xlm_portuguese_e8_all","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_pretrained_xlm_portuguese_e8_all|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/harish/preTrained-xlm-pt-e8-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_pretrained_xlm_portuguese_e8_all_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_pretrained_xlm_portuguese_e8_all_pipeline_en.md
new file mode 100644
index 00000000000000..8f7860c53a80b4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_pretrained_xlm_portuguese_e8_all_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_pretrained_xlm_portuguese_e8_all_pipeline pipeline XlmRoBertaSentenceEmbeddings from harish
+author: John Snow Labs
+name: sent_pretrained_xlm_portuguese_e8_all_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_pretrained_xlm_portuguese_e8_all_pipeline` is a English model originally trained by harish.
+
+{:.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/sent_pretrained_xlm_portuguese_e8_all_pipeline_en_5.5.0_3.0_1725813493514.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_pretrained_xlm_portuguese_e8_all_pipeline_en_5.5.0_3.0_1725813493514.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
+
+pipeline = PretrainedPipeline("sent_pretrained_xlm_portuguese_e8_all_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_pretrained_xlm_portuguese_e8_all_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_pretrained_xlm_portuguese_e8_all_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/harish/preTrained-xlm-pt-e8-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_tamil_bert_pipeline_ta.md b/docs/_posts/ahmedlone127/2024-09-08-sent_tamil_bert_pipeline_ta.md
new file mode 100644
index 00000000000000..8fc90c3e52b8ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_tamil_bert_pipeline_ta.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Tamil sent_tamil_bert_pipeline pipeline BertSentenceEmbeddings from l3cube-pune
+author: John Snow Labs
+name: sent_tamil_bert_pipeline
+date: 2024-09-08
+tags: [ta, open_source, pipeline, onnx]
+task: Embeddings
+language: ta
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_tamil_bert_pipeline` is a Tamil model originally trained by l3cube-pune.
+
+{:.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/sent_tamil_bert_pipeline_ta_5.5.0_3.0_1725791246464.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_tamil_bert_pipeline_ta_5.5.0_3.0_1725791246464.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
+
+pipeline = PretrainedPipeline("sent_tamil_bert_pipeline", lang = "ta")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_tamil_bert_pipeline", lang = "ta")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_tamil_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ta|
+|Size:|891.2 MB|
+
+## References
+
+https://huggingface.co/l3cube-pune/tamil-bert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_tiny_clinicalbert_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_tiny_clinicalbert_en.md
new file mode 100644
index 00000000000000..8e05a40ca5bb47
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_tiny_clinicalbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_tiny_clinicalbert BertSentenceEmbeddings from nlpie
+author: John Snow Labs
+name: sent_tiny_clinicalbert
+date: 2024-09-08
+tags: [en, open_source, onnx, sentence_embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertSentenceEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_tiny_clinicalbert` is a English model originally trained by nlpie.
+
+{:.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/sent_tiny_clinicalbert_en_5.5.0_3.0_1725790763343.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_tiny_clinicalbert_en_5.5.0_3.0_1725790763343.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = BertSentenceEmbeddings.pretrained("sent_tiny_clinicalbert","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = BertSentenceEmbeddings.pretrained("sent_tiny_clinicalbert","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_tiny_clinicalbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|51.9 MB|
+
+## References
+
+https://huggingface.co/nlpie/tiny-clinicalbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_tiny_clinicalbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_tiny_clinicalbert_pipeline_en.md
new file mode 100644
index 00000000000000..623f56d4e8484b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_tiny_clinicalbert_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_tiny_clinicalbert_pipeline pipeline BertSentenceEmbeddings from nlpie
+author: John Snow Labs
+name: sent_tiny_clinicalbert_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_tiny_clinicalbert_pipeline` is a English model originally trained by nlpie.
+
+{:.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/sent_tiny_clinicalbert_pipeline_en_5.5.0_3.0_1725790766448.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_tiny_clinicalbert_pipeline_en_5.5.0_3.0_1725790766448.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
+
+pipeline = PretrainedPipeline("sent_tiny_clinicalbert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_tiny_clinicalbert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_tiny_clinicalbert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|52.5 MB|
+
+## References
+
+https://huggingface.co/nlpie/tiny-clinicalbert
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- BertSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_translit_ppa_northern_sami_asian_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-08-sent_translit_ppa_northern_sami_asian_pipeline_xx.md
new file mode 100644
index 00000000000000..ae6c9f0280d15f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_translit_ppa_northern_sami_asian_pipeline_xx.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: Multilingual sent_translit_ppa_northern_sami_asian_pipeline pipeline XlmRoBertaSentenceEmbeddings from orxhelili
+author: John Snow Labs
+name: sent_translit_ppa_northern_sami_asian_pipeline
+date: 2024-09-08
+tags: [xx, open_source, pipeline, onnx]
+task: Embeddings
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_translit_ppa_northern_sami_asian_pipeline` is a Multilingual model originally trained by orxhelili.
+
+{:.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/sent_translit_ppa_northern_sami_asian_pipeline_xx_5.5.0_3.0_1725759326481.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_translit_ppa_northern_sami_asian_pipeline_xx_5.5.0_3.0_1725759326481.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
+
+pipeline = PretrainedPipeline("sent_translit_ppa_northern_sami_asian_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_translit_ppa_northern_sami_asian_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_translit_ppa_northern_sami_asian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/orxhelili/translit_ppa_se_asian
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_xlm_r_with_transliteration_max_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_xlm_r_with_transliteration_max_en.md
new file mode 100644
index 00000000000000..8ee89471a66a70
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_xlm_r_with_transliteration_max_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlm_r_with_transliteration_max XlmRoBertaSentenceEmbeddings from yihongLiu
+author: John Snow Labs
+name: sent_xlm_r_with_transliteration_max
+date: 2024-09-08
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+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.`sent_xlm_r_with_transliteration_max` is a English model originally trained by yihongLiu.
+
+{:.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/sent_xlm_r_with_transliteration_max_en_5.5.0_3.0_1725763423997.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_r_with_transliteration_max_en_5.5.0_3.0_1725763423997.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_r_with_transliteration_max","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_r_with_transliteration_max","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_r_with_transliteration_max|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|843.3 MB|
+
+## References
+
+https://huggingface.co/yihongLiu/xlm-r-with-transliteration-max
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_xlm_roberta_base_finetuned_amharic_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_xlm_roberta_base_finetuned_amharic_en.md
new file mode 100644
index 00000000000000..6b57f41c07a84a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_xlm_roberta_base_finetuned_amharic_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_amharic XlmRoBertaSentenceEmbeddings from Davlan
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_amharic
+date: 2024-09-08
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+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.`sent_xlm_roberta_base_finetuned_amharic` is a English model originally trained by Davlan.
+
+{:.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/sent_xlm_roberta_base_finetuned_amharic_en_5.5.0_3.0_1725759090010.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_amharic_en_5.5.0_3.0_1725759090010.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_amharic","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_amharic","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_amharic|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-amharic
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_xlm_roberta_base_finetuned_burmese_dear_watson2_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_xlm_roberta_base_finetuned_burmese_dear_watson2_en.md
new file mode 100644
index 00000000000000..7a492310a44f51
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_xlm_roberta_base_finetuned_burmese_dear_watson2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_burmese_dear_watson2 XlmRoBertaSentenceEmbeddings from SmartPy
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_burmese_dear_watson2
+date: 2024-09-08
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+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.`sent_xlm_roberta_base_finetuned_burmese_dear_watson2` is a English model originally trained by SmartPy.
+
+{:.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/sent_xlm_roberta_base_finetuned_burmese_dear_watson2_en_5.5.0_3.0_1725813295968.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_burmese_dear_watson2_en_5.5.0_3.0_1725813295968.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_burmese_dear_watson2","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_burmese_dear_watson2","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_burmese_dear_watson2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/SmartPy/xlm-roberta-base-finetuned-my_dear_watson2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_xlm_roberta_base_finetuned_kinyarwanda_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_xlm_roberta_base_finetuned_kinyarwanda_en.md
new file mode 100644
index 00000000000000..8358212b566b61
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_xlm_roberta_base_finetuned_kinyarwanda_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_kinyarwanda XlmRoBertaSentenceEmbeddings from Davlan
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_kinyarwanda
+date: 2024-09-08
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+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.`sent_xlm_roberta_base_finetuned_kinyarwanda` is a English model originally trained by Davlan.
+
+{:.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/sent_xlm_roberta_base_finetuned_kinyarwanda_en_5.5.0_3.0_1725797339471.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_kinyarwanda_en_5.5.0_3.0_1725797339471.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_kinyarwanda","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_kinyarwanda","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_kinyarwanda|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-kinyarwanda
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned_en.md
new file mode 100644
index 00000000000000..925d302b4d95cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned XlmRoBertaSentenceEmbeddings from RogerB
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned
+date: 2024-09-08
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+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.`sent_xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned` is a English model originally trained by RogerB.
+
+{:.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/sent_xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned_en_5.5.0_3.0_1725813290894.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned_en_5.5.0_3.0_1725813290894.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_kinyarwanda_kinre_finetuned|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/RogerB/xlm-roberta-base-finetuned-kinyarwanda-kinre-finetuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_xlm_roberta_base_finetuned_kinyarwanda_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_xlm_roberta_base_finetuned_kinyarwanda_pipeline_en.md
new file mode 100644
index 00000000000000..7e824f28d7975f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_xlm_roberta_base_finetuned_kinyarwanda_pipeline_en.md
@@ -0,0 +1,71 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_finetuned_kinyarwanda_pipeline pipeline XlmRoBertaSentenceEmbeddings from Davlan
+author: John Snow Labs
+name: sent_xlm_roberta_base_finetuned_kinyarwanda_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_xlm_roberta_base_finetuned_kinyarwanda_pipeline` is a English model originally trained by Davlan.
+
+{:.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/sent_xlm_roberta_base_finetuned_kinyarwanda_pipeline_en_5.5.0_3.0_1725797387939.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_finetuned_kinyarwanda_pipeline_en_5.5.0_3.0_1725797387939.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
+
+pipeline = PretrainedPipeline("sent_xlm_roberta_base_finetuned_kinyarwanda_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sent_xlm_roberta_base_finetuned_kinyarwanda_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_finetuned_kinyarwanda_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-kinyarwanda
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- SentenceDetectorDLModel
+- XlmRoBertaSentenceEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sent_xlm_roberta_base_yelp_mlm_en.md b/docs/_posts/ahmedlone127/2024-09-08-sent_xlm_roberta_base_yelp_mlm_en.md
new file mode 100644
index 00000000000000..fa807010d34f47
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sent_xlm_roberta_base_yelp_mlm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sent_xlm_roberta_base_yelp_mlm XlmRoBertaSentenceEmbeddings from Yaxin
+author: John Snow Labs
+name: sent_xlm_roberta_base_yelp_mlm
+date: 2024-09-08
+tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+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.`sent_xlm_roberta_base_yelp_mlm` is a English model originally trained by Yaxin.
+
+{:.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/sent_xlm_roberta_base_yelp_mlm_en_5.5.0_3.0_1725762735439.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_yelp_mlm_en_5.5.0_3.0_1725762735439.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("sentence")
+
+embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_yelp_mlm","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base_yelp_mlm","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sent_xlm_roberta_base_yelp_mlm|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentence]|
+|Output Labels:|[embeddings]|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Yaxin/xlm-roberta-base-yelp-mlm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sentiment_analysis_fine_tuned_3000samples_en.md b/docs/_posts/ahmedlone127/2024-09-08-sentiment_analysis_fine_tuned_3000samples_en.md
new file mode 100644
index 00000000000000..d545387edc7016
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sentiment_analysis_fine_tuned_3000samples_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sentiment_analysis_fine_tuned_3000samples DistilBertForSequenceClassification from alexander2023
+author: John Snow Labs
+name: sentiment_analysis_fine_tuned_3000samples
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_analysis_fine_tuned_3000samples` is a English model originally trained by alexander2023.
+
+{:.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/sentiment_analysis_fine_tuned_3000samples_en_5.5.0_3.0_1725774965934.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_analysis_fine_tuned_3000samples_en_5.5.0_3.0_1725774965934.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("sentiment_analysis_fine_tuned_3000samples","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("sentiment_analysis_fine_tuned_3000samples", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_analysis_fine_tuned_3000samples|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/alexander2023/Sentiment-Analysis-Fine-Tuned-3000Samples
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sentiment_analysis_ninja_en.md b/docs/_posts/ahmedlone127/2024-09-08-sentiment_analysis_ninja_en.md
new file mode 100644
index 00000000000000..27c3ffbf83b855
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sentiment_analysis_ninja_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sentiment_analysis_ninja BertForSequenceClassification from ninja
+author: John Snow Labs
+name: sentiment_analysis_ninja
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_analysis_ninja` is a English model originally trained by ninja.
+
+{:.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/sentiment_analysis_ninja_en_5.5.0_3.0_1725825726168.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_analysis_ninja_en_5.5.0_3.0_1725825726168.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("sentiment_analysis_ninja","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("sentiment_analysis_ninja", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_analysis_ninja|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/ninja/Sentiment_Analysis
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sentiment_analysis_roberta_bases_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-sentiment_analysis_roberta_bases_pipeline_en.md
new file mode 100644
index 00000000000000..ed91cb4a961780
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sentiment_analysis_roberta_bases_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sentiment_analysis_roberta_bases_pipeline pipeline RoBertaForSequenceClassification from Winnie-Kay
+author: John Snow Labs
+name: sentiment_analysis_roberta_bases_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_analysis_roberta_bases_pipeline` is a English model originally trained by Winnie-Kay.
+
+{:.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/sentiment_analysis_roberta_bases_pipeline_en_5.5.0_3.0_1725830887509.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_analysis_roberta_bases_pipeline_en_5.5.0_3.0_1725830887509.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
+
+pipeline = PretrainedPipeline("sentiment_analysis_roberta_bases_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sentiment_analysis_roberta_bases_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_analysis_roberta_bases_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|444.0 MB|
+
+## References
+
+https://huggingface.co/Winnie-Kay/Sentiment-Analysis-Roberta-bases
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sentiment_roberta_clean_e8_b16_data2_en.md b/docs/_posts/ahmedlone127/2024-09-08-sentiment_roberta_clean_e8_b16_data2_en.md
new file mode 100644
index 00000000000000..52e629ad708aa9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sentiment_roberta_clean_e8_b16_data2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sentiment_roberta_clean_e8_b16_data2 RoBertaForSequenceClassification from JerryYanJiang
+author: John Snow Labs
+name: sentiment_roberta_clean_e8_b16_data2
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_roberta_clean_e8_b16_data2` is a English model originally trained by JerryYanJiang.
+
+{:.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/sentiment_roberta_clean_e8_b16_data2_en_5.5.0_3.0_1725820557837.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_roberta_clean_e8_b16_data2_en_5.5.0_3.0_1725820557837.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("sentiment_roberta_clean_e8_b16_data2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("sentiment_roberta_clean_e8_b16_data2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_roberta_clean_e8_b16_data2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/JerryYanJiang/sentiment-roberta-clean-e8-b16-data2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sentiment_roberta_clean_e8_b16_data2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-sentiment_roberta_clean_e8_b16_data2_pipeline_en.md
new file mode 100644
index 00000000000000..df4dafe5909c4a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sentiment_roberta_clean_e8_b16_data2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sentiment_roberta_clean_e8_b16_data2_pipeline pipeline RoBertaForSequenceClassification from JerryYanJiang
+author: John Snow Labs
+name: sentiment_roberta_clean_e8_b16_data2_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_roberta_clean_e8_b16_data2_pipeline` is a English model originally trained by JerryYanJiang.
+
+{:.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/sentiment_roberta_clean_e8_b16_data2_pipeline_en_5.5.0_3.0_1725820630251.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_roberta_clean_e8_b16_data2_pipeline_en_5.5.0_3.0_1725820630251.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
+
+pipeline = PretrainedPipeline("sentiment_roberta_clean_e8_b16_data2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sentiment_roberta_clean_e8_b16_data2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentiment_roberta_clean_e8_b16_data2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/JerryYanJiang/sentiment-roberta-clean-e8-b16-data2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-setfit_ethos_multilabel_example_clp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-setfit_ethos_multilabel_example_clp_pipeline_en.md
new file mode 100644
index 00000000000000..7b0f3efdb75de7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-setfit_ethos_multilabel_example_clp_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English setfit_ethos_multilabel_example_clp_pipeline pipeline MPNetEmbeddings from clp
+author: John Snow Labs
+name: setfit_ethos_multilabel_example_clp_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_ethos_multilabel_example_clp_pipeline` is a English model originally trained by clp.
+
+{:.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/setfit_ethos_multilabel_example_clp_pipeline_en_5.5.0_3.0_1725815277101.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_ethos_multilabel_example_clp_pipeline_en_5.5.0_3.0_1725815277101.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
+
+pipeline = PretrainedPipeline("setfit_ethos_multilabel_example_clp_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("setfit_ethos_multilabel_example_clp_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|setfit_ethos_multilabel_example_clp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.0 MB|
+
+## References
+
+https://huggingface.co/clp/setfit-ethos-multilabel-example
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-setfit_model_feb11_misinformation_on_media_traditional_social_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-setfit_model_feb11_misinformation_on_media_traditional_social_pipeline_en.md
new file mode 100644
index 00000000000000..aff1b3aa5ebbed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-setfit_model_feb11_misinformation_on_media_traditional_social_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English setfit_model_feb11_misinformation_on_media_traditional_social_pipeline pipeline MPNetEmbeddings from mitra-mir
+author: John Snow Labs
+name: setfit_model_feb11_misinformation_on_media_traditional_social_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_model_feb11_misinformation_on_media_traditional_social_pipeline` is a English model originally trained by mitra-mir.
+
+{:.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/setfit_model_feb11_misinformation_on_media_traditional_social_pipeline_en_5.5.0_3.0_1725817545365.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_model_feb11_misinformation_on_media_traditional_social_pipeline_en_5.5.0_3.0_1725817545365.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
+
+pipeline = PretrainedPipeline("setfit_model_feb11_misinformation_on_media_traditional_social_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("setfit_model_feb11_misinformation_on_media_traditional_social_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|setfit_model_feb11_misinformation_on_media_traditional_social_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/mitra-mir/setfit-model-Feb11-Misinformation-on-Media-Traditional-Social
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-setfit_model_ireland_binary_label1_epochs2_feb_28_2023_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-setfit_model_ireland_binary_label1_epochs2_feb_28_2023_pipeline_en.md
new file mode 100644
index 00000000000000..b16689cc635a10
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-setfit_model_ireland_binary_label1_epochs2_feb_28_2023_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English setfit_model_ireland_binary_label1_epochs2_feb_28_2023_pipeline pipeline MPNetEmbeddings from mitra-mir
+author: John Snow Labs
+name: setfit_model_ireland_binary_label1_epochs2_feb_28_2023_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_model_ireland_binary_label1_epochs2_feb_28_2023_pipeline` is a English model originally trained by mitra-mir.
+
+{:.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/setfit_model_ireland_binary_label1_epochs2_feb_28_2023_pipeline_en_5.5.0_3.0_1725769219672.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_model_ireland_binary_label1_epochs2_feb_28_2023_pipeline_en_5.5.0_3.0_1725769219672.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
+
+pipeline = PretrainedPipeline("setfit_model_ireland_binary_label1_epochs2_feb_28_2023_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("setfit_model_ireland_binary_label1_epochs2_feb_28_2023_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|setfit_model_ireland_binary_label1_epochs2_feb_28_2023_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/mitra-mir/setfit_model_Ireland_binary_label1_epochs2_Feb_28_2023
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-setfit_zero_shot_classification_pbsp_p3_freq_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-setfit_zero_shot_classification_pbsp_p3_freq_pipeline_en.md
new file mode 100644
index 00000000000000..644dc15688d3dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-setfit_zero_shot_classification_pbsp_p3_freq_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English setfit_zero_shot_classification_pbsp_p3_freq_pipeline pipeline MPNetEmbeddings from aammari
+author: John Snow Labs
+name: setfit_zero_shot_classification_pbsp_p3_freq_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_zero_shot_classification_pbsp_p3_freq_pipeline` is a English model originally trained by aammari.
+
+{:.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/setfit_zero_shot_classification_pbsp_p3_freq_pipeline_en_5.5.0_3.0_1725817548529.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_zero_shot_classification_pbsp_p3_freq_pipeline_en_5.5.0_3.0_1725817548529.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
+
+pipeline = PretrainedPipeline("setfit_zero_shot_classification_pbsp_p3_freq_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("setfit_zero_shot_classification_pbsp_p3_freq_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|setfit_zero_shot_classification_pbsp_p3_freq_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/aammari/setfit-zero-shot-classification-pbsp-p3-freq
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-setfitbcmpii_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-setfitbcmpii_pipeline_en.md
new file mode 100644
index 00000000000000..72ac26360fc9a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-setfitbcmpii_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English setfitbcmpii_pipeline pipeline MPNetEmbeddings from mann2107
+author: John Snow Labs
+name: setfitbcmpii_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfitbcmpii_pipeline` is a English model originally trained by mann2107.
+
+{:.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/setfitbcmpii_pipeline_en_5.5.0_3.0_1725815692890.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfitbcmpii_pipeline_en_5.5.0_3.0_1725815692890.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
+
+pipeline = PretrainedPipeline("setfitbcmpii_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("setfitbcmpii_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|setfitbcmpii_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/mann2107/setfitbcmpii
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sinbert_sold_sinhalese_std_0_01_en.md b/docs/_posts/ahmedlone127/2024-09-08-sinbert_sold_sinhalese_std_0_01_en.md
new file mode 100644
index 00000000000000..e502d4db59f19d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sinbert_sold_sinhalese_std_0_01_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sinbert_sold_sinhalese_std_0_01 RoBertaForSequenceClassification from sinhala-nlp
+author: John Snow Labs
+name: sinbert_sold_sinhalese_std_0_01
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sinbert_sold_sinhalese_std_0_01` is a English model originally trained by sinhala-nlp.
+
+{:.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/sinbert_sold_sinhalese_std_0_01_en_5.5.0_3.0_1725830236986.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sinbert_sold_sinhalese_std_0_01_en_5.5.0_3.0_1725830236986.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("sinbert_sold_sinhalese_std_0_01","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("sinbert_sold_sinhalese_std_0_01", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sinbert_sold_sinhalese_std_0_01|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|472.7 MB|
+
+## References
+
+https://huggingface.co/sinhala-nlp/sinbert-sold-si-std-0.01
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sinbert_sold_sinhalese_std_0_01_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-sinbert_sold_sinhalese_std_0_01_pipeline_en.md
new file mode 100644
index 00000000000000..e1c67f4a1ec857
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sinbert_sold_sinhalese_std_0_01_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sinbert_sold_sinhalese_std_0_01_pipeline pipeline RoBertaForSequenceClassification from sinhala-nlp
+author: John Snow Labs
+name: sinbert_sold_sinhalese_std_0_01_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sinbert_sold_sinhalese_std_0_01_pipeline` is a English model originally trained by sinhala-nlp.
+
+{:.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/sinbert_sold_sinhalese_std_0_01_pipeline_en_5.5.0_3.0_1725830260345.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sinbert_sold_sinhalese_std_0_01_pipeline_en_5.5.0_3.0_1725830260345.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
+
+pipeline = PretrainedPipeline("sinbert_sold_sinhalese_std_0_01_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sinbert_sold_sinhalese_std_0_01_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sinbert_sold_sinhalese_std_0_01_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|472.8 MB|
+
+## References
+
+https://huggingface.co/sinhala-nlp/sinbert-sold-si-std-0.01
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sloberta_20480_pretrained_50e_en.md b/docs/_posts/ahmedlone127/2024-09-08-sloberta_20480_pretrained_50e_en.md
new file mode 100644
index 00000000000000..2e4376af19ba74
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sloberta_20480_pretrained_50e_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sloberta_20480_pretrained_50e CamemBertEmbeddings from bcolnar
+author: John Snow Labs
+name: sloberta_20480_pretrained_50e
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sloberta_20480_pretrained_50e` is a English model originally trained by bcolnar.
+
+{:.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/sloberta_20480_pretrained_50e_en_5.5.0_3.0_1725786397562.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sloberta_20480_pretrained_50e_en_5.5.0_3.0_1725786397562.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("sloberta_20480_pretrained_50e","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("sloberta_20480_pretrained_50e","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sloberta_20480_pretrained_50e|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|469.0 MB|
+
+## References
+
+https://huggingface.co/bcolnar/sloberta-20480-pretrained-50e
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sloberta_20480_pretrained_50e_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-sloberta_20480_pretrained_50e_pipeline_en.md
new file mode 100644
index 00000000000000..c56b43f68810c6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sloberta_20480_pretrained_50e_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sloberta_20480_pretrained_50e_pipeline pipeline CamemBertEmbeddings from bcolnar
+author: John Snow Labs
+name: sloberta_20480_pretrained_50e_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sloberta_20480_pretrained_50e_pipeline` is a English model originally trained by bcolnar.
+
+{:.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/sloberta_20480_pretrained_50e_pipeline_en_5.5.0_3.0_1725786419297.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sloberta_20480_pretrained_50e_pipeline_en_5.5.0_3.0_1725786419297.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
+
+pipeline = PretrainedPipeline("sloberta_20480_pretrained_50e_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sloberta_20480_pretrained_50e_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sloberta_20480_pretrained_50e_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|469.0 MB|
+
+## References
+
+https://huggingface.co/bcolnar/sloberta-20480-pretrained-50e
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-smol8_en.md b/docs/_posts/ahmedlone127/2024-09-08-smol8_en.md
new file mode 100644
index 00000000000000..97c30628575686
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-smol8_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English smol8 MPNetEmbeddings from Watwat100
+author: John Snow Labs
+name: smol8
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`smol8` is a English model originally trained by Watwat100.
+
+{:.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/smol8_en_5.5.0_3.0_1725815113964.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/smol8_en_5.5.0_3.0_1725815113964.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("smol8","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("smol8","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|smol8|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/Watwat100/smol8
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-smol8_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-smol8_pipeline_en.md
new file mode 100644
index 00000000000000..4be2ce0daf4f92
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-smol8_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English smol8_pipeline pipeline MPNetEmbeddings from Watwat100
+author: John Snow Labs
+name: smol8_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`smol8_pipeline` is a English model originally trained by Watwat100.
+
+{:.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/smol8_pipeline_en_5.5.0_3.0_1725815138732.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/smol8_pipeline_en_5.5.0_3.0_1725815138732.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
+
+pipeline = PretrainedPipeline("smol8_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("smol8_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|smol8_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/Watwat100/smol8
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sms_spam_detection_bertforsequenceclassification_en.md b/docs/_posts/ahmedlone127/2024-09-08-sms_spam_detection_bertforsequenceclassification_en.md
new file mode 100644
index 00000000000000..f75096a771656d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sms_spam_detection_bertforsequenceclassification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English sms_spam_detection_bertforsequenceclassification BertForSequenceClassification from andresar1205
+author: John Snow Labs
+name: sms_spam_detection_bertforsequenceclassification
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sms_spam_detection_bertforsequenceclassification` is a English model originally trained by andresar1205.
+
+{:.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/sms_spam_detection_bertforsequenceclassification_en_5.5.0_3.0_1725818940471.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sms_spam_detection_bertforsequenceclassification_en_5.5.0_3.0_1725818940471.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("sms_spam_detection_bertforsequenceclassification","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("sms_spam_detection_bertforsequenceclassification", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sms_spam_detection_bertforsequenceclassification|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/andresar1205/SMS-spam-detection-BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-sms_spam_detection_bertforsequenceclassification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-sms_spam_detection_bertforsequenceclassification_pipeline_en.md
new file mode 100644
index 00000000000000..ac0c9aaef1bfff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-sms_spam_detection_bertforsequenceclassification_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sms_spam_detection_bertforsequenceclassification_pipeline pipeline BertForSequenceClassification from andresar1205
+author: John Snow Labs
+name: sms_spam_detection_bertforsequenceclassification_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sms_spam_detection_bertforsequenceclassification_pipeline` is a English model originally trained by andresar1205.
+
+{:.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/sms_spam_detection_bertforsequenceclassification_pipeline_en_5.5.0_3.0_1725818960852.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sms_spam_detection_bertforsequenceclassification_pipeline_en_5.5.0_3.0_1725818960852.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
+
+pipeline = PretrainedPipeline("sms_spam_detection_bertforsequenceclassification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sms_spam_detection_bertforsequenceclassification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sms_spam_detection_bertforsequenceclassification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/andresar1205/SMS-spam-detection-BertForSequenceClassification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-southern_sotho_all_mpnet_finetuned_comb_4500_en.md b/docs/_posts/ahmedlone127/2024-09-08-southern_sotho_all_mpnet_finetuned_comb_4500_en.md
new file mode 100644
index 00000000000000..fb660b67f4bdaf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-southern_sotho_all_mpnet_finetuned_comb_4500_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English southern_sotho_all_mpnet_finetuned_comb_4500 MPNetEmbeddings from danfeg
+author: John Snow Labs
+name: southern_sotho_all_mpnet_finetuned_comb_4500
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`southern_sotho_all_mpnet_finetuned_comb_4500` is a English model originally trained by danfeg.
+
+{:.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/southern_sotho_all_mpnet_finetuned_comb_4500_en_5.5.0_3.0_1725815801528.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/southern_sotho_all_mpnet_finetuned_comb_4500_en_5.5.0_3.0_1725815801528.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("southern_sotho_all_mpnet_finetuned_comb_4500","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("southern_sotho_all_mpnet_finetuned_comb_4500","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|southern_sotho_all_mpnet_finetuned_comb_4500|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/danfeg/ST-ALL-MPNET_Finetuned-COMB-4500
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-southern_sotho_all_mpnet_finetuned_comb_6000_en.md b/docs/_posts/ahmedlone127/2024-09-08-southern_sotho_all_mpnet_finetuned_comb_6000_en.md
new file mode 100644
index 00000000000000..348427f71b5b67
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-southern_sotho_all_mpnet_finetuned_comb_6000_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English southern_sotho_all_mpnet_finetuned_comb_6000 MPNetEmbeddings from danfeg
+author: John Snow Labs
+name: southern_sotho_all_mpnet_finetuned_comb_6000
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`southern_sotho_all_mpnet_finetuned_comb_6000` is a English model originally trained by danfeg.
+
+{:.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/southern_sotho_all_mpnet_finetuned_comb_6000_en_5.5.0_3.0_1725769197633.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/southern_sotho_all_mpnet_finetuned_comb_6000_en_5.5.0_3.0_1725769197633.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("southern_sotho_all_mpnet_finetuned_comb_6000","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("southern_sotho_all_mpnet_finetuned_comb_6000","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|southern_sotho_all_mpnet_finetuned_comb_6000|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/danfeg/ST-ALL-MPNET_Finetuned-COMB-6000
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-southern_sotho_all_mpnet_finetuned_english_2481_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-southern_sotho_all_mpnet_finetuned_english_2481_pipeline_en.md
new file mode 100644
index 00000000000000..42c17916978c43
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-southern_sotho_all_mpnet_finetuned_english_2481_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English southern_sotho_all_mpnet_finetuned_english_2481_pipeline pipeline MPNetEmbeddings from danfeg
+author: John Snow Labs
+name: southern_sotho_all_mpnet_finetuned_english_2481_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`southern_sotho_all_mpnet_finetuned_english_2481_pipeline` is a English model originally trained by danfeg.
+
+{:.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/southern_sotho_all_mpnet_finetuned_english_2481_pipeline_en_5.5.0_3.0_1725769770854.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/southern_sotho_all_mpnet_finetuned_english_2481_pipeline_en_5.5.0_3.0_1725769770854.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
+
+pipeline = PretrainedPipeline("southern_sotho_all_mpnet_finetuned_english_2481_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("southern_sotho_all_mpnet_finetuned_english_2481_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|southern_sotho_all_mpnet_finetuned_english_2481_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.8 MB|
+
+## References
+
+https://huggingface.co/danfeg/ST-ALL-MPNET_Finetuned-EN-2481
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-southern_sotho_english_50_en.md b/docs/_posts/ahmedlone127/2024-09-08-southern_sotho_english_50_en.md
new file mode 100644
index 00000000000000..305ef8945931e0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-southern_sotho_english_50_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English southern_sotho_english_50 MarianTransformer from cw1521
+author: John Snow Labs
+name: southern_sotho_english_50
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`southern_sotho_english_50` is a English model originally trained by cw1521.
+
+{:.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/southern_sotho_english_50_en_5.5.0_3.0_1725795511763.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/southern_sotho_english_50_en_5.5.0_3.0_1725795511763.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("southern_sotho_english_50","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("southern_sotho_english_50","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|southern_sotho_english_50|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.6 MB|
+
+## References
+
+https://huggingface.co/cw1521/st-en-50
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-spark_name_burmese_tonga_tonga_islands_english_en.md b/docs/_posts/ahmedlone127/2024-09-08-spark_name_burmese_tonga_tonga_islands_english_en.md
new file mode 100644
index 00000000000000..2a896f9d3e1a88
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-spark_name_burmese_tonga_tonga_islands_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English spark_name_burmese_tonga_tonga_islands_english MarianTransformer from ihebaker10
+author: John Snow Labs
+name: spark_name_burmese_tonga_tonga_islands_english
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spark_name_burmese_tonga_tonga_islands_english` is a English model originally trained by ihebaker10.
+
+{:.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/spark_name_burmese_tonga_tonga_islands_english_en_5.5.0_3.0_1725766044908.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spark_name_burmese_tonga_tonga_islands_english_en_5.5.0_3.0_1725766044908.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("spark_name_burmese_tonga_tonga_islands_english","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("spark_name_burmese_tonga_tonga_islands_english","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|spark_name_burmese_tonga_tonga_islands_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|532.7 MB|
+
+## References
+
+https://huggingface.co/ihebaker10/spark-name-my-to-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-spea_1_en.md b/docs/_posts/ahmedlone127/2024-09-08-spea_1_en.md
new file mode 100644
index 00000000000000..876abe83c1f6a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-spea_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English spea_1 RoBertaForSequenceClassification from BaronSch
+author: John Snow Labs
+name: spea_1
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spea_1` is a English model originally trained by BaronSch.
+
+{:.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/spea_1_en_5.5.0_3.0_1725821136442.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spea_1_en_5.5.0_3.0_1725821136442.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("spea_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("spea_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|spea_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|468.5 MB|
+
+## References
+
+https://huggingface.co/BaronSch/Spea_1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-spea_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-spea_1_pipeline_en.md
new file mode 100644
index 00000000000000..5fadf0a24dae9f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-spea_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English spea_1_pipeline pipeline RoBertaForSequenceClassification from BaronSch
+author: John Snow Labs
+name: spea_1_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spea_1_pipeline` is a English model originally trained by BaronSch.
+
+{:.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/spea_1_pipeline_en_5.5.0_3.0_1725821159541.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spea_1_pipeline_en_5.5.0_3.0_1725821159541.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
+
+pipeline = PretrainedPipeline("spea_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("spea_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|spea_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.5 MB|
+
+## References
+
+https://huggingface.co/BaronSch/Spea_1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-spotify_podcast_advertising_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-spotify_podcast_advertising_classification_pipeline_en.md
new file mode 100644
index 00000000000000..8a114d2d283625
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-spotify_podcast_advertising_classification_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English spotify_podcast_advertising_classification_pipeline pipeline BertForSequenceClassification from morenolq
+author: John Snow Labs
+name: spotify_podcast_advertising_classification_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spotify_podcast_advertising_classification_pipeline` is a English model originally trained by morenolq.
+
+{:.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/spotify_podcast_advertising_classification_pipeline_en_5.5.0_3.0_1725761535653.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spotify_podcast_advertising_classification_pipeline_en_5.5.0_3.0_1725761535653.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
+
+pipeline = PretrainedPipeline("spotify_podcast_advertising_classification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("spotify_podcast_advertising_classification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|spotify_podcast_advertising_classification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|405.9 MB|
+
+## References
+
+https://huggingface.co/morenolq/spotify-podcast-advertising-classification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-stego_classifier_checkpoint_epoch_10_2024_07_26_14_26_52_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-stego_classifier_checkpoint_epoch_10_2024_07_26_14_26_52_pipeline_en.md
new file mode 100644
index 00000000000000..9fccb4dc81904d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-stego_classifier_checkpoint_epoch_10_2024_07_26_14_26_52_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English stego_classifier_checkpoint_epoch_10_2024_07_26_14_26_52_pipeline pipeline DistilBertForSequenceClassification from jvelja
+author: John Snow Labs
+name: stego_classifier_checkpoint_epoch_10_2024_07_26_14_26_52_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`stego_classifier_checkpoint_epoch_10_2024_07_26_14_26_52_pipeline` is a English model originally trained by jvelja.
+
+{:.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/stego_classifier_checkpoint_epoch_10_2024_07_26_14_26_52_pipeline_en_5.5.0_3.0_1725775560828.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/stego_classifier_checkpoint_epoch_10_2024_07_26_14_26_52_pipeline_en_5.5.0_3.0_1725775560828.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
+
+pipeline = PretrainedPipeline("stego_classifier_checkpoint_epoch_10_2024_07_26_14_26_52_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("stego_classifier_checkpoint_epoch_10_2024_07_26_14_26_52_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|stego_classifier_checkpoint_epoch_10_2024_07_26_14_26_52_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jvelja/stego-classifier-checkpoint-epoch-10-2024-07-26_14-26-52
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-stego_classifier_checkpoint_epoch_60_2024_07_26_16_03_28_en.md b/docs/_posts/ahmedlone127/2024-09-08-stego_classifier_checkpoint_epoch_60_2024_07_26_16_03_28_en.md
new file mode 100644
index 00000000000000..892b96f81c9c9e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-stego_classifier_checkpoint_epoch_60_2024_07_26_16_03_28_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English stego_classifier_checkpoint_epoch_60_2024_07_26_16_03_28 DistilBertForSequenceClassification from jvelja
+author: John Snow Labs
+name: stego_classifier_checkpoint_epoch_60_2024_07_26_16_03_28
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`stego_classifier_checkpoint_epoch_60_2024_07_26_16_03_28` is a English model originally trained by jvelja.
+
+{:.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/stego_classifier_checkpoint_epoch_60_2024_07_26_16_03_28_en_5.5.0_3.0_1725774853991.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/stego_classifier_checkpoint_epoch_60_2024_07_26_16_03_28_en_5.5.0_3.0_1725774853991.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("stego_classifier_checkpoint_epoch_60_2024_07_26_16_03_28","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("stego_classifier_checkpoint_epoch_60_2024_07_26_16_03_28", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|stego_classifier_checkpoint_epoch_60_2024_07_26_16_03_28|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/jvelja/stego-classifier-checkpoint-epoch-60-2024-07-26_16-03-28
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-student_marian_english_romanian_6_3_en.md b/docs/_posts/ahmedlone127/2024-09-08-student_marian_english_romanian_6_3_en.md
new file mode 100644
index 00000000000000..7eba1232be7a2e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-student_marian_english_romanian_6_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English student_marian_english_romanian_6_3 MarianTransformer from sshleifer
+author: John Snow Labs
+name: student_marian_english_romanian_6_3
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`student_marian_english_romanian_6_3` is a English model originally trained by sshleifer.
+
+{:.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/student_marian_english_romanian_6_3_en_5.5.0_3.0_1725795821425.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/student_marian_english_romanian_6_3_en_5.5.0_3.0_1725795821425.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("student_marian_english_romanian_6_3","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("student_marian_english_romanian_6_3","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|student_marian_english_romanian_6_3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|291.5 MB|
+
+## References
+
+https://huggingface.co/sshleifer/student_marian_en_ro_6_3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-task_implicit_task__model_deberta__aug_method_bt_en.md b/docs/_posts/ahmedlone127/2024-09-08-task_implicit_task__model_deberta__aug_method_bt_en.md
new file mode 100644
index 00000000000000..96a210d861168d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-task_implicit_task__model_deberta__aug_method_bt_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English task_implicit_task__model_deberta__aug_method_bt DeBertaForSequenceClassification from BenjaminOcampo
+author: John Snow Labs
+name: task_implicit_task__model_deberta__aug_method_bt
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`task_implicit_task__model_deberta__aug_method_bt` is a English model originally trained by BenjaminOcampo.
+
+{:.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/task_implicit_task__model_deberta__aug_method_bt_en_5.5.0_3.0_1725803780286.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/task_implicit_task__model_deberta__aug_method_bt_en_5.5.0_3.0_1725803780286.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("task_implicit_task__model_deberta__aug_method_bt","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("task_implicit_task__model_deberta__aug_method_bt", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|task_implicit_task__model_deberta__aug_method_bt|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|607.5 MB|
+
+## References
+
+https://huggingface.co/BenjaminOcampo/task-implicit_task__model-deberta__aug_method-bt
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-task_implicit_task__model_deberta__aug_method_bt_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-task_implicit_task__model_deberta__aug_method_bt_pipeline_en.md
new file mode 100644
index 00000000000000..a75270833952a5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-task_implicit_task__model_deberta__aug_method_bt_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English task_implicit_task__model_deberta__aug_method_bt_pipeline pipeline DeBertaForSequenceClassification from BenjaminOcampo
+author: John Snow Labs
+name: task_implicit_task__model_deberta__aug_method_bt_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`task_implicit_task__model_deberta__aug_method_bt_pipeline` is a English model originally trained by BenjaminOcampo.
+
+{:.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/task_implicit_task__model_deberta__aug_method_bt_pipeline_en_5.5.0_3.0_1725803822445.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/task_implicit_task__model_deberta__aug_method_bt_pipeline_en_5.5.0_3.0_1725803822445.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
+
+pipeline = PretrainedPipeline("task_implicit_task__model_deberta__aug_method_bt_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("task_implicit_task__model_deberta__aug_method_bt_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|task_implicit_task__model_deberta__aug_method_bt_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|607.5 MB|
+
+## References
+
+https://huggingface.co/BenjaminOcampo/task-implicit_task__model-deberta__aug_method-bt
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-task_implicit_task__model_deberta__aug_method_gm_revised_en.md b/docs/_posts/ahmedlone127/2024-09-08-task_implicit_task__model_deberta__aug_method_gm_revised_en.md
new file mode 100644
index 00000000000000..6affa3d82a801b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-task_implicit_task__model_deberta__aug_method_gm_revised_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English task_implicit_task__model_deberta__aug_method_gm_revised DeBertaForSequenceClassification from BenjaminOcampo
+author: John Snow Labs
+name: task_implicit_task__model_deberta__aug_method_gm_revised
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`task_implicit_task__model_deberta__aug_method_gm_revised` is a English model originally trained by BenjaminOcampo.
+
+{:.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/task_implicit_task__model_deberta__aug_method_gm_revised_en_5.5.0_3.0_1725811557274.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/task_implicit_task__model_deberta__aug_method_gm_revised_en_5.5.0_3.0_1725811557274.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("task_implicit_task__model_deberta__aug_method_gm_revised","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("task_implicit_task__model_deberta__aug_method_gm_revised", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|task_implicit_task__model_deberta__aug_method_gm_revised|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|607.4 MB|
+
+## References
+
+https://huggingface.co/BenjaminOcampo/task-implicit_task__model-deberta__aug_method-gm_revised
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-task_implicit_task__model_deberta__aug_method_gm_revised_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-task_implicit_task__model_deberta__aug_method_gm_revised_pipeline_en.md
new file mode 100644
index 00000000000000..b8707c757f6558
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-task_implicit_task__model_deberta__aug_method_gm_revised_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English task_implicit_task__model_deberta__aug_method_gm_revised_pipeline pipeline DeBertaForSequenceClassification from BenjaminOcampo
+author: John Snow Labs
+name: task_implicit_task__model_deberta__aug_method_gm_revised_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`task_implicit_task__model_deberta__aug_method_gm_revised_pipeline` is a English model originally trained by BenjaminOcampo.
+
+{:.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/task_implicit_task__model_deberta__aug_method_gm_revised_pipeline_en_5.5.0_3.0_1725811596136.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/task_implicit_task__model_deberta__aug_method_gm_revised_pipeline_en_5.5.0_3.0_1725811596136.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
+
+pipeline = PretrainedPipeline("task_implicit_task__model_deberta__aug_method_gm_revised_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("task_implicit_task__model_deberta__aug_method_gm_revised_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|task_implicit_task__model_deberta__aug_method_gm_revised_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|607.4 MB|
+
+## References
+
+https://huggingface.co/BenjaminOcampo/task-implicit_task__model-deberta__aug_method-gm_revised
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-tec19_qa_en2th_maltese_en.md b/docs/_posts/ahmedlone127/2024-09-08-tec19_qa_en2th_maltese_en.md
new file mode 100644
index 00000000000000..2bcaf9e39b4333
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-tec19_qa_en2th_maltese_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English tec19_qa_en2th_maltese MarianTransformer from ManaponS
+author: John Snow Labs
+name: tec19_qa_en2th_maltese
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tec19_qa_en2th_maltese` is a English model originally trained by ManaponS.
+
+{:.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/tec19_qa_en2th_maltese_en_5.5.0_3.0_1725796182495.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tec19_qa_en2th_maltese_en_5.5.0_3.0_1725796182495.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("tec19_qa_en2th_maltese","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("tec19_qa_en2th_maltese","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tec19_qa_en2th_maltese|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|530.2 MB|
+
+## References
+
+https://huggingface.co/ManaponS/TEC19-QA_EN2TH_MT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-tec19_qa_en2th_maltese_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-tec19_qa_en2th_maltese_pipeline_en.md
new file mode 100644
index 00000000000000..211138cc012b22
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-tec19_qa_en2th_maltese_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English tec19_qa_en2th_maltese_pipeline pipeline MarianTransformer from ManaponS
+author: John Snow Labs
+name: tec19_qa_en2th_maltese_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tec19_qa_en2th_maltese_pipeline` is a English model originally trained by ManaponS.
+
+{:.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/tec19_qa_en2th_maltese_pipeline_en_5.5.0_3.0_1725796209626.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tec19_qa_en2th_maltese_pipeline_en_5.5.0_3.0_1725796209626.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
+
+pipeline = PretrainedPipeline("tec19_qa_en2th_maltese_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tec19_qa_en2th_maltese_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tec19_qa_en2th_maltese_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|530.7 MB|
+
+## References
+
+https://huggingface.co/ManaponS/TEC19-QA_EN2TH_MT
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-test1_en.md b/docs/_posts/ahmedlone127/2024-09-08-test1_en.md
new file mode 100644
index 00000000000000..de7b630babdcdf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-test1_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English test1 DistilBertForQuestionAnswering from ManaponS
+author: John Snow Labs
+name: test1
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test1` is a English model originally trained by ManaponS.
+
+{:.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/test1_en_5.5.0_3.0_1725818518077.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test1_en_5.5.0_3.0_1725818518077.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("test1","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("test1", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/ManaponS/Test1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-test1_finetuned_kde4_english_tonga_tonga_islands_italian_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-test1_finetuned_kde4_english_tonga_tonga_islands_italian_pipeline_en.md
new file mode 100644
index 00000000000000..538ed87f9b222a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-test1_finetuned_kde4_english_tonga_tonga_islands_italian_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English test1_finetuned_kde4_english_tonga_tonga_islands_italian_pipeline pipeline MarianTransformer from sarrabenrejeb
+author: John Snow Labs
+name: test1_finetuned_kde4_english_tonga_tonga_islands_italian_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test1_finetuned_kde4_english_tonga_tonga_islands_italian_pipeline` is a English model originally trained by sarrabenrejeb.
+
+{:.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/test1_finetuned_kde4_english_tonga_tonga_islands_italian_pipeline_en_5.5.0_3.0_1725766420863.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test1_finetuned_kde4_english_tonga_tonga_islands_italian_pipeline_en_5.5.0_3.0_1725766420863.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
+
+pipeline = PretrainedPipeline("test1_finetuned_kde4_english_tonga_tonga_islands_italian_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test1_finetuned_kde4_english_tonga_tonga_islands_italian_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test1_finetuned_kde4_english_tonga_tonga_islands_italian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|623.5 MB|
+
+## References
+
+https://huggingface.co/sarrabenrejeb/test1-finetuned-kde4-en-to-it
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-test1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-test1_pipeline_en.md
new file mode 100644
index 00000000000000..982b96d77e02ff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-test1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English test1_pipeline pipeline DistilBertForQuestionAnswering from ManaponS
+author: John Snow Labs
+name: test1_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test1_pipeline` is a English model originally trained by ManaponS.
+
+{:.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/test1_pipeline_en_5.5.0_3.0_1725818530374.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test1_pipeline_en_5.5.0_3.0_1725818530374.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
+
+pipeline = PretrainedPipeline("test1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/ManaponS/Test1
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-test_hf_distil_bert_toxic_df_en.md b/docs/_posts/ahmedlone127/2024-09-08-test_hf_distil_bert_toxic_df_en.md
new file mode 100644
index 00000000000000..b7742daeec5442
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-test_hf_distil_bert_toxic_df_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English test_hf_distil_bert_toxic_df DistilBertForSequenceClassification from AgneyPraseed
+author: John Snow Labs
+name: test_hf_distil_bert_toxic_df
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_hf_distil_bert_toxic_df` is a English model originally trained by AgneyPraseed.
+
+{:.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/test_hf_distil_bert_toxic_df_en_5.5.0_3.0_1725808393800.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_hf_distil_bert_toxic_df_en_5.5.0_3.0_1725808393800.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("test_hf_distil_bert_toxic_df","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("test_hf_distil_bert_toxic_df", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_hf_distil_bert_toxic_df|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/AgneyPraseed/test_hf_distil_bert_toxic_df
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-test_model_12944qwerty_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-test_model_12944qwerty_pipeline_en.md
new file mode 100644
index 00000000000000..2bbb6e7d40e14a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-test_model_12944qwerty_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English test_model_12944qwerty_pipeline pipeline DistilBertForQuestionAnswering from 12944qwerty
+author: John Snow Labs
+name: test_model_12944qwerty_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_model_12944qwerty_pipeline` is a English model originally trained by 12944qwerty.
+
+{:.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/test_model_12944qwerty_pipeline_en_5.5.0_3.0_1725798034716.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_model_12944qwerty_pipeline_en_5.5.0_3.0_1725798034716.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
+
+pipeline = PretrainedPipeline("test_model_12944qwerty_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test_model_12944qwerty_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_model_12944qwerty_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/12944qwerty/test_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-test_model_en.md b/docs/_posts/ahmedlone127/2024-09-08-test_model_en.md
new file mode 100644
index 00000000000000..a466564d8998f6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-test_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English test_model MPNetEmbeddings from Linco
+author: John Snow Labs
+name: test_model
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`test_model` is a English model originally trained by Linco.
+
+{:.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/test_model_en_5.5.0_3.0_1725816557709.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_model_en_5.5.0_3.0_1725816557709.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("test_model","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("test_model","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/Linco/test-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-test_model_lori0330_en.md b/docs/_posts/ahmedlone127/2024-09-08-test_model_lori0330_en.md
new file mode 100644
index 00000000000000..00257779ae5e36
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-test_model_lori0330_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English test_model_lori0330 DistilBertForSequenceClassification from lori0330
+author: John Snow Labs
+name: test_model_lori0330
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_model_lori0330` is a English model originally trained by lori0330.
+
+{:.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/test_model_lori0330_en_5.5.0_3.0_1725809006864.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_model_lori0330_en_5.5.0_3.0_1725809006864.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("test_model_lori0330","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("test_model_lori0330", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_model_lori0330|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lori0330/test-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-test_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-test_model_pipeline_en.md
new file mode 100644
index 00000000000000..94f3db3edae35f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-test_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English test_model_pipeline pipeline MPNetEmbeddings from Linco
+author: John Snow Labs
+name: test_model_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_model_pipeline` is a English model originally trained by Linco.
+
+{:.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/test_model_pipeline_en_5.5.0_3.0_1725816585757.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_model_pipeline_en_5.5.0_3.0_1725816585757.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
+
+pipeline = PretrainedPipeline("test_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("test_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/Linco/test-model
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-test_setfit_model_menbom_en.md b/docs/_posts/ahmedlone127/2024-09-08-test_setfit_model_menbom_en.md
new file mode 100644
index 00000000000000..cce11f47a6de35
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-test_setfit_model_menbom_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English test_setfit_model_menbom MPNetEmbeddings from menbom
+author: John Snow Labs
+name: test_setfit_model_menbom
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`test_setfit_model_menbom` is a English model originally trained by menbom.
+
+{:.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/test_setfit_model_menbom_en_5.5.0_3.0_1725817391551.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_setfit_model_menbom_en_5.5.0_3.0_1725817391551.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("test_setfit_model_menbom","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("test_setfit_model_menbom","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|test_setfit_model_menbom|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.9 MB|
+
+## References
+
+https://huggingface.co/menbom/test-setfit-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-testing1_anni000_en.md b/docs/_posts/ahmedlone127/2024-09-08-testing1_anni000_en.md
new file mode 100644
index 00000000000000..08361f38fb54e3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-testing1_anni000_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English testing1_anni000 DistilBertForSequenceClassification from Anni000
+author: John Snow Labs
+name: testing1_anni000
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`testing1_anni000` is a English model originally trained by Anni000.
+
+{:.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/testing1_anni000_en_5.5.0_3.0_1725808613936.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/testing1_anni000_en_5.5.0_3.0_1725808613936.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("testing1_anni000","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("testing1_anni000", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|testing1_anni000|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Anni000/testing1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-testing_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-testing_pipeline_en.md
new file mode 100644
index 00000000000000..e51d8085d205e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-testing_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English testing_pipeline pipeline RoBertaForSequenceClassification from NoCaptain
+author: John Snow Labs
+name: testing_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`testing_pipeline` is a English model originally trained by NoCaptain.
+
+{:.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/testing_pipeline_en_5.5.0_3.0_1725779150290.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/testing_pipeline_en_5.5.0_3.0_1725779150290.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
+
+pipeline = PretrainedPipeline("testing_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("testing_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|testing_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|309.1 MB|
+
+## References
+
+https://huggingface.co/NoCaptain/TESTING
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-text_class_emotion_en.md b/docs/_posts/ahmedlone127/2024-09-08-text_class_emotion_en.md
new file mode 100644
index 00000000000000..4b3d9059ee6ff9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-text_class_emotion_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English text_class_emotion RoBertaForSequenceClassification from DonzerHD
+author: John Snow Labs
+name: text_class_emotion
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`text_class_emotion` is a English model originally trained by DonzerHD.
+
+{:.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/text_class_emotion_en_5.5.0_3.0_1725830380418.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/text_class_emotion_en_5.5.0_3.0_1725830380418.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("text_class_emotion","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("text_class_emotion", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|text_class_emotion|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|308.5 MB|
+
+## References
+
+https://huggingface.co/DonzerHD/text_class_emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-text_class_emotion_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-text_class_emotion_pipeline_en.md
new file mode 100644
index 00000000000000..b8739b1584189a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-text_class_emotion_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English text_class_emotion_pipeline pipeline RoBertaForSequenceClassification from DonzerHD
+author: John Snow Labs
+name: text_class_emotion_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`text_class_emotion_pipeline` is a English model originally trained by DonzerHD.
+
+{:.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/text_class_emotion_pipeline_en_5.5.0_3.0_1725830396089.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/text_class_emotion_pipeline_en_5.5.0_3.0_1725830396089.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
+
+pipeline = PretrainedPipeline("text_class_emotion_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("text_class_emotion_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|text_class_emotion_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|308.5 MB|
+
+## References
+
+https://huggingface.co/DonzerHD/text_class_emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-textfooler_roberta_base_boolq_en.md b/docs/_posts/ahmedlone127/2024-09-08-textfooler_roberta_base_boolq_en.md
new file mode 100644
index 00000000000000..4ef3ce87fe735b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-textfooler_roberta_base_boolq_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English textfooler_roberta_base_boolq RoBertaForSequenceClassification from korca
+author: John Snow Labs
+name: textfooler_roberta_base_boolq
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`textfooler_roberta_base_boolq` is a English model originally trained by korca.
+
+{:.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/textfooler_roberta_base_boolq_en_5.5.0_3.0_1725829719050.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/textfooler_roberta_base_boolq_en_5.5.0_3.0_1725829719050.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("textfooler_roberta_base_boolq","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("textfooler_roberta_base_boolq", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|textfooler_roberta_base_boolq|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|463.2 MB|
+
+## References
+
+https://huggingface.co/korca/textfooler-roberta-base-boolq
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-textpara_qa_model_en.md b/docs/_posts/ahmedlone127/2024-09-08-textpara_qa_model_en.md
new file mode 100644
index 00000000000000..94ee738d66d270
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-textpara_qa_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English textpara_qa_model DistilBertForQuestionAnswering from vishal2002
+author: John Snow Labs
+name: textpara_qa_model
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`textpara_qa_model` is a English model originally trained by vishal2002.
+
+{:.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/textpara_qa_model_en_5.5.0_3.0_1725817998859.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/textpara_qa_model_en_5.5.0_3.0_1725817998859.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("textpara_qa_model","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("textpara_qa_model", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|textpara_qa_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/vishal2002/textPara_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-textpara_qa_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-textpara_qa_model_pipeline_en.md
new file mode 100644
index 00000000000000..e8dc037fbfd551
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-textpara_qa_model_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English textpara_qa_model_pipeline pipeline DistilBertForQuestionAnswering from vishal2002
+author: John Snow Labs
+name: textpara_qa_model_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`textpara_qa_model_pipeline` is a English model originally trained by vishal2002.
+
+{:.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/textpara_qa_model_pipeline_en_5.5.0_3.0_1725818013023.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/textpara_qa_model_pipeline_en_5.5.0_3.0_1725818013023.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
+
+pipeline = PretrainedPipeline("textpara_qa_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("textpara_qa_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|textpara_qa_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/vishal2002/textPara_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-tipo_campanya_ong_v3_en.md b/docs/_posts/ahmedlone127/2024-09-08-tipo_campanya_ong_v3_en.md
new file mode 100644
index 00000000000000..db4b4d9f110d05
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-tipo_campanya_ong_v3_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English tipo_campanya_ong_v3 MPNetEmbeddings from api19750904
+author: John Snow Labs
+name: tipo_campanya_ong_v3
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`tipo_campanya_ong_v3` is a English model originally trained by api19750904.
+
+{:.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/tipo_campanya_ong_v3_en_5.5.0_3.0_1725816714704.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tipo_campanya_ong_v3_en_5.5.0_3.0_1725816714704.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("tipo_campanya_ong_v3","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("tipo_campanya_ong_v3","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tipo_campanya_ong_v3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.2 MB|
+
+## References
+
+https://huggingface.co/api19750904/tipo_campanya_ong_v3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-tmp_trainer_ubermenchh_en.md b/docs/_posts/ahmedlone127/2024-09-08-tmp_trainer_ubermenchh_en.md
new file mode 100644
index 00000000000000..ff47fe7f95205d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-tmp_trainer_ubermenchh_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English tmp_trainer_ubermenchh DistilBertForSequenceClassification from ubermenchh
+author: John Snow Labs
+name: tmp_trainer_ubermenchh
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tmp_trainer_ubermenchh` is a English model originally trained by ubermenchh.
+
+{:.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/tmp_trainer_ubermenchh_en_5.5.0_3.0_1725777314222.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tmp_trainer_ubermenchh_en_5.5.0_3.0_1725777314222.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("tmp_trainer_ubermenchh","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("tmp_trainer_ubermenchh", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tmp_trainer_ubermenchh|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/ubermenchh/tmp_trainer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-token_classification_model_jethrowang_en.md b/docs/_posts/ahmedlone127/2024-09-08-token_classification_model_jethrowang_en.md
new file mode 100644
index 00000000000000..6253c4b7a82c0f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-token_classification_model_jethrowang_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English token_classification_model_jethrowang DistilBertForTokenClassification from jethrowang
+author: John Snow Labs
+name: token_classification_model_jethrowang
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`token_classification_model_jethrowang` is a English model originally trained by jethrowang.
+
+{:.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/token_classification_model_jethrowang_en_5.5.0_3.0_1725788883065.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/token_classification_model_jethrowang_en_5.5.0_3.0_1725788883065.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("token_classification_model_jethrowang","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("token_classification_model_jethrowang", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|token_classification_model_jethrowang|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/jethrowang/token_classification_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-token_classification_model_vishnun0027_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-token_classification_model_vishnun0027_pipeline_en.md
new file mode 100644
index 00000000000000..006c5f28513024
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-token_classification_model_vishnun0027_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English token_classification_model_vishnun0027_pipeline pipeline DistilBertForTokenClassification from vishnun0027
+author: John Snow Labs
+name: token_classification_model_vishnun0027_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`token_classification_model_vishnun0027_pipeline` is a English model originally trained by vishnun0027.
+
+{:.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/token_classification_model_vishnun0027_pipeline_en_5.5.0_3.0_1725788388699.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/token_classification_model_vishnun0027_pipeline_en_5.5.0_3.0_1725788388699.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
+
+pipeline = PretrainedPipeline("token_classification_model_vishnun0027_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("token_classification_model_vishnun0027_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|token_classification_model_vishnun0027_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/vishnun0027/token_classification_model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-token_classification_test_psehgal_en.md b/docs/_posts/ahmedlone127/2024-09-08-token_classification_test_psehgal_en.md
new file mode 100644
index 00000000000000..79723db2cf98dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-token_classification_test_psehgal_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English token_classification_test_psehgal DistilBertForTokenClassification from psehgal
+author: John Snow Labs
+name: token_classification_test_psehgal
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`token_classification_test_psehgal` is a English model originally trained by psehgal.
+
+{:.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/token_classification_test_psehgal_en_5.5.0_3.0_1725827789167.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/token_classification_test_psehgal_en_5.5.0_3.0_1725827789167.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("token_classification_test_psehgal","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("token_classification_test_psehgal", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|token_classification_test_psehgal|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.4 MB|
+
+## References
+
+https://huggingface.co/psehgal/token_classification_test
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-topic_civil_rights_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-topic_civil_rights_pipeline_en.md
new file mode 100644
index 00000000000000..82076a892a8620
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-topic_civil_rights_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English topic_civil_rights_pipeline pipeline RoBertaForSequenceClassification from dell-research-harvard
+author: John Snow Labs
+name: topic_civil_rights_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`topic_civil_rights_pipeline` is a English model originally trained by dell-research-harvard.
+
+{:.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/topic_civil_rights_pipeline_en_5.5.0_3.0_1725820972087.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/topic_civil_rights_pipeline_en_5.5.0_3.0_1725820972087.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
+
+pipeline = PretrainedPipeline("topic_civil_rights_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("topic_civil_rights_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|topic_civil_rights_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/dell-research-harvard/topic-civil_rights
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-topic_crime_en.md b/docs/_posts/ahmedlone127/2024-09-08-topic_crime_en.md
new file mode 100644
index 00000000000000..9dfcd527770e72
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-topic_crime_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English topic_crime RoBertaForSequenceClassification from dell-research-harvard
+author: John Snow Labs
+name: topic_crime
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`topic_crime` is a English model originally trained by dell-research-harvard.
+
+{:.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/topic_crime_en_5.5.0_3.0_1725821413733.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/topic_crime_en_5.5.0_3.0_1725821413733.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("topic_crime","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("topic_crime", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|topic_crime|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/dell-research-harvard/topic-crime
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-topic_protests_en.md b/docs/_posts/ahmedlone127/2024-09-08-topic_protests_en.md
new file mode 100644
index 00000000000000..bd9f6c505b09e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-topic_protests_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English topic_protests RoBertaForSequenceClassification from dell-research-harvard
+author: John Snow Labs
+name: topic_protests
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`topic_protests` is a English model originally trained by dell-research-harvard.
+
+{:.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/topic_protests_en_5.5.0_3.0_1725831002467.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/topic_protests_en_5.5.0_3.0_1725831002467.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("topic_protests","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("topic_protests", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|topic_protests|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|309.0 MB|
+
+## References
+
+https://huggingface.co/dell-research-harvard/topic-protests
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-topic_protests_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-topic_protests_pipeline_en.md
new file mode 100644
index 00000000000000..742fa45300baa6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-topic_protests_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English topic_protests_pipeline pipeline RoBertaForSequenceClassification from dell-research-harvard
+author: John Snow Labs
+name: topic_protests_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`topic_protests_pipeline` is a English model originally trained by dell-research-harvard.
+
+{:.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/topic_protests_pipeline_en_5.5.0_3.0_1725831018234.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/topic_protests_pipeline_en_5.5.0_3.0_1725831018234.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
+
+pipeline = PretrainedPipeline("topic_protests_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("topic_protests_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|topic_protests_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|309.1 MB|
+
+## References
+
+https://huggingface.co/dell-research-harvard/topic-protests
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-tounsify_v0_10_shuffle_en.md b/docs/_posts/ahmedlone127/2024-09-08-tounsify_v0_10_shuffle_en.md
new file mode 100644
index 00000000000000..66888f55ced963
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-tounsify_v0_10_shuffle_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English tounsify_v0_10_shuffle MarianTransformer from cherifkhalifah
+author: John Snow Labs
+name: tounsify_v0_10_shuffle
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tounsify_v0_10_shuffle` is a English model originally trained by cherifkhalifah.
+
+{:.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/tounsify_v0_10_shuffle_en_5.5.0_3.0_1725795824715.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tounsify_v0_10_shuffle_en_5.5.0_3.0_1725795824715.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("tounsify_v0_10_shuffle","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("tounsify_v0_10_shuffle","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tounsify_v0_10_shuffle|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|528.3 MB|
+
+## References
+
+https://huggingface.co/cherifkhalifah/Tounsify-v0.10-shuffle
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-traduttore_english_italian_2_en.md b/docs/_posts/ahmedlone127/2024-09-08-traduttore_english_italian_2_en.md
new file mode 100644
index 00000000000000..ee3b359993089c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-traduttore_english_italian_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English traduttore_english_italian_2 MarianTransformer from zaneas
+author: John Snow Labs
+name: traduttore_english_italian_2
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`traduttore_english_italian_2` is a English model originally trained by zaneas.
+
+{:.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/traduttore_english_italian_2_en_5.5.0_3.0_1725795951633.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/traduttore_english_italian_2_en_5.5.0_3.0_1725795951633.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("traduttore_english_italian_2","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("traduttore_english_italian_2","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|traduttore_english_italian_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|622.9 MB|
+
+## References
+
+https://huggingface.co/zaneas/Traduttore_EN_IT_2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-traduttore_english_italian_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-traduttore_english_italian_2_pipeline_en.md
new file mode 100644
index 00000000000000..b6f091538c127b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-traduttore_english_italian_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English traduttore_english_italian_2_pipeline pipeline MarianTransformer from zaneas
+author: John Snow Labs
+name: traduttore_english_italian_2_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`traduttore_english_italian_2_pipeline` is a English model originally trained by zaneas.
+
+{:.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/traduttore_english_italian_2_pipeline_en_5.5.0_3.0_1725795981984.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/traduttore_english_italian_2_pipeline_en_5.5.0_3.0_1725795981984.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
+
+pipeline = PretrainedPipeline("traduttore_english_italian_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("traduttore_english_italian_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|traduttore_english_italian_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|623.5 MB|
+
+## References
+
+https://huggingface.co/zaneas/Traduttore_EN_IT_2
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-trainedsentiment_en.md b/docs/_posts/ahmedlone127/2024-09-08-trainedsentiment_en.md
new file mode 100644
index 00000000000000..544d153b648879
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-trainedsentiment_en.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: English trainedsentiment DistilBertForSequenceClassification from comp1mp
+author: John Snow Labs
+name: trainedsentiment
+date: 2024-09-08
+tags: [bert, en, open_source, sequence_classification, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trainedsentiment` is a English model originally trained by comp1mp.
+
+## 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/trainedsentiment_en_5.5.0_3.0_1725777069235.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trainedsentiment_en_5.5.0_3.0_1725777069235.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("document")
+
+tokenizer = Tokenizer()\
+    .setInputCols("document")\
+    .setOutputCol("token")  
+    
+sequenceClassifier = DistilBertForSequenceClassification.pretrained("trainedsentiment","en")\
+            .setInputCols(["document","token"])\
+            .setOutputCol("class")
+
+pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text")
+    .setOutputCol("document")
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document") 
+    .setOutputCol("token")  
+    
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("trainedsentiment","en")
+            .setInputCols(Array("document","token"))
+            .setOutputCol("class")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trainedsentiment|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+References
+
+https://huggingface.co/comp1mp/trainedsentiment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-trainedsentiment_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-trainedsentiment_pipeline_en.md
new file mode 100644
index 00000000000000..6cd4ce38f1936c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-trainedsentiment_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English trainedsentiment_pipeline pipeline DistilBertForSequenceClassification from PathofthePeople
+author: John Snow Labs
+name: trainedsentiment_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trainedsentiment_pipeline` is a English model originally trained by PathofthePeople.
+
+{:.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/trainedsentiment_pipeline_en_5.5.0_3.0_1725777081444.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trainedsentiment_pipeline_en_5.5.0_3.0_1725777081444.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
+
+pipeline = PretrainedPipeline("trainedsentiment_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("trainedsentiment_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trainedsentiment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/PathofthePeople/TrainedSentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-trainer_f_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-trainer_f_pipeline_en.md
new file mode 100644
index 00000000000000..c0c80fb2b8d18b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-trainer_f_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English trainer_f_pipeline pipeline DistilBertForSequenceClassification from SimoneJLaudani
+author: John Snow Labs
+name: trainer_f_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trainer_f_pipeline` is a English model originally trained by SimoneJLaudani.
+
+{:.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/trainer_f_pipeline_en_5.5.0_3.0_1725808519158.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trainer_f_pipeline_en_5.5.0_3.0_1725808519158.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
+
+pipeline = PretrainedPipeline("trainer_f_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("trainer_f_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trainer_f_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/SimoneJLaudani/trainer_f
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-trainer_output_dir_en.md b/docs/_posts/ahmedlone127/2024-09-08-trainer_output_dir_en.md
new file mode 100644
index 00000000000000..974dbdb0f18d1d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-trainer_output_dir_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English trainer_output_dir DistilBertForSequenceClassification from sunithapillai
+author: John Snow Labs
+name: trainer_output_dir
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trainer_output_dir` is a English model originally trained by sunithapillai.
+
+{:.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/trainer_output_dir_en_5.5.0_3.0_1725775033108.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trainer_output_dir_en_5.5.0_3.0_1725775033108.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("trainer_output_dir","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("trainer_output_dir", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trainer_output_dir|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|250.4 MB|
+
+## References
+
+https://huggingface.co/sunithapillai/trainer_output_dir
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-trans_english_vietnamese_v1_en.md b/docs/_posts/ahmedlone127/2024-09-08-trans_english_vietnamese_v1_en.md
new file mode 100644
index 00000000000000..39fdc076cd7b24
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-trans_english_vietnamese_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English trans_english_vietnamese_v1 MarianTransformer from B2111797
+author: John Snow Labs
+name: trans_english_vietnamese_v1
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trans_english_vietnamese_v1` is a English model originally trained by B2111797.
+
+{:.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/trans_english_vietnamese_v1_en_5.5.0_3.0_1725832531062.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trans_english_vietnamese_v1_en_5.5.0_3.0_1725832531062.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("trans_english_vietnamese_v1","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("trans_english_vietnamese_v1","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trans_english_vietnamese_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|474.9 MB|
+
+## References
+
+https://huggingface.co/B2111797/trans-en-vi-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-trans_english_vietnamese_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-trans_english_vietnamese_v1_pipeline_en.md
new file mode 100644
index 00000000000000..6cd40753819ba2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-trans_english_vietnamese_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English trans_english_vietnamese_v1_pipeline pipeline MarianTransformer from B2111797
+author: John Snow Labs
+name: trans_english_vietnamese_v1_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trans_english_vietnamese_v1_pipeline` is a English model originally trained by B2111797.
+
+{:.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/trans_english_vietnamese_v1_pipeline_en_5.5.0_3.0_1725832554079.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trans_english_vietnamese_v1_pipeline_en_5.5.0_3.0_1725832554079.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
+
+pipeline = PretrainedPipeline("trans_english_vietnamese_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("trans_english_vietnamese_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trans_english_vietnamese_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|475.4 MB|
+
+## References
+
+https://huggingface.co/B2111797/trans-en-vi-v1
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-translateen_arabic_en.md b/docs/_posts/ahmedlone127/2024-09-08-translateen_arabic_en.md
new file mode 100644
index 00000000000000..c735f0eb9f66a5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-translateen_arabic_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English translateen_arabic MarianTransformer from shahad-alh
+author: John Snow Labs
+name: translateen_arabic
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`translateen_arabic` is a English model originally trained by shahad-alh.
+
+{:.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/translateen_arabic_en_5.5.0_3.0_1725832128001.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/translateen_arabic_en_5.5.0_3.0_1725832128001.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("translateen_arabic","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("translateen_arabic","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|translateen_arabic|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|528.0 MB|
+
+## References
+
+https://huggingface.co/shahad-alh/translateEN_AR
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-translation_20_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-translation_20_pipeline_en.md
new file mode 100644
index 00000000000000..23eb9bc6186243
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-translation_20_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English translation_20_pipeline pipeline MarianTransformer from dammyogt
+author: John Snow Labs
+name: translation_20_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`translation_20_pipeline` is a English model originally trained by dammyogt.
+
+{:.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/translation_20_pipeline_en_5.5.0_3.0_1725831326339.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/translation_20_pipeline_en_5.5.0_3.0_1725831326339.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
+
+pipeline = PretrainedPipeline("translation_20_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("translation_20_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|translation_20_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|498.4 MB|
+
+## References
+
+https://huggingface.co/dammyogt/translation_20
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-translation_english_tonga_tonga_islands_turkish_1_en.md b/docs/_posts/ahmedlone127/2024-09-08-translation_english_tonga_tonga_islands_turkish_1_en.md
new file mode 100644
index 00000000000000..923617743b8c73
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-translation_english_tonga_tonga_islands_turkish_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English translation_english_tonga_tonga_islands_turkish_1 MarianTransformer from verach3n
+author: John Snow Labs
+name: translation_english_tonga_tonga_islands_turkish_1
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`translation_english_tonga_tonga_islands_turkish_1` is a English model originally trained by verach3n.
+
+{:.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/translation_english_tonga_tonga_islands_turkish_1_en_5.5.0_3.0_1725796034741.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/translation_english_tonga_tonga_islands_turkish_1_en_5.5.0_3.0_1725796034741.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("translation_english_tonga_tonga_islands_turkish_1","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("translation_english_tonga_tonga_islands_turkish_1","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|translation_english_tonga_tonga_islands_turkish_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|509.7 MB|
+
+## References
+
+https://huggingface.co/verach3n/translation-en-to-tr-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-translation_korean_english_en.md b/docs/_posts/ahmedlone127/2024-09-08-translation_korean_english_en.md
new file mode 100644
index 00000000000000..3b64d9d3fbdc54
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-translation_korean_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English translation_korean_english MarianTransformer from halee9
+author: John Snow Labs
+name: translation_korean_english
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`translation_korean_english` is a English model originally trained by halee9.
+
+{:.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/translation_korean_english_en_5.5.0_3.0_1725765722423.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/translation_korean_english_en_5.5.0_3.0_1725765722423.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("translation_korean_english","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("translation_korean_english","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|translation_korean_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|540.8 MB|
+
+## References
+
+https://huggingface.co/halee9/translation_ko_en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-translation_korean_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-translation_korean_english_pipeline_en.md
new file mode 100644
index 00000000000000..18cdb1013d51e8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-translation_korean_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English translation_korean_english_pipeline pipeline MarianTransformer from halee9
+author: John Snow Labs
+name: translation_korean_english_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`translation_korean_english_pipeline` is a English model originally trained by halee9.
+
+{:.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/translation_korean_english_pipeline_en_5.5.0_3.0_1725765752362.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/translation_korean_english_pipeline_en_5.5.0_3.0_1725765752362.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
+
+pipeline = PretrainedPipeline("translation_korean_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("translation_korean_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|translation_korean_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|541.3 MB|
+
+## References
+
+https://huggingface.co/halee9/translation_ko_en
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-trust_clf_merged_dataset_xlm_roberta_longformer_base_4096_4bins_5epochs_en.md b/docs/_posts/ahmedlone127/2024-09-08-trust_clf_merged_dataset_xlm_roberta_longformer_base_4096_4bins_5epochs_en.md
new file mode 100644
index 00000000000000..81a3086fe94cc0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-trust_clf_merged_dataset_xlm_roberta_longformer_base_4096_4bins_5epochs_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English trust_clf_merged_dataset_xlm_roberta_longformer_base_4096_4bins_5epochs XlmRoBertaForSequenceClassification from luisespinosa
+author: John Snow Labs
+name: trust_clf_merged_dataset_xlm_roberta_longformer_base_4096_4bins_5epochs
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trust_clf_merged_dataset_xlm_roberta_longformer_base_4096_4bins_5epochs` is a English model originally trained by luisespinosa.
+
+{:.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/trust_clf_merged_dataset_xlm_roberta_longformer_base_4096_4bins_5epochs_en_5.5.0_3.0_1725781409061.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trust_clf_merged_dataset_xlm_roberta_longformer_base_4096_4bins_5epochs_en_5.5.0_3.0_1725781409061.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("trust_clf_merged_dataset_xlm_roberta_longformer_base_4096_4bins_5epochs","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("trust_clf_merged_dataset_xlm_roberta_longformer_base_4096_4bins_5epochs", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|trust_clf_merged_dataset_xlm_roberta_longformer_base_4096_4bins_5epochs|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/luisespinosa/trust-clf-merged_dataset_xlm-roberta-longformer-base-4096_4bins_5epochs
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-turkish_bert_6493_5411_5464_v3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-turkish_bert_6493_5411_5464_v3_pipeline_en.md
new file mode 100644
index 00000000000000..7b1077bce3da52
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-turkish_bert_6493_5411_5464_v3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English turkish_bert_6493_5411_5464_v3_pipeline pipeline BertForSequenceClassification from muhammtcelik
+author: John Snow Labs
+name: turkish_bert_6493_5411_5464_v3_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkish_bert_6493_5411_5464_v3_pipeline` is a English model originally trained by muhammtcelik.
+
+{:.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/turkish_bert_6493_5411_5464_v3_pipeline_en_5.5.0_3.0_1725819613832.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkish_bert_6493_5411_5464_v3_pipeline_en_5.5.0_3.0_1725819613832.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
+
+pipeline = PretrainedPipeline("turkish_bert_6493_5411_5464_v3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("turkish_bert_6493_5411_5464_v3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|turkish_bert_6493_5411_5464_v3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|415.5 MB|
+
+## References
+
+https://huggingface.co/muhammtcelik/turkish-bert-6493-5411-5464_v3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-turkishnermodel_en.md b/docs/_posts/ahmedlone127/2024-09-08-turkishnermodel_en.md
new file mode 100644
index 00000000000000..3bf969d7aa0e15
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-turkishnermodel_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English turkishnermodel BertForTokenClassification from MesutAktas
+author: John Snow Labs
+name: turkishnermodel
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkishnermodel` is a English model originally trained by MesutAktas.
+
+{:.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/turkishnermodel_en_5.5.0_3.0_1725822040381.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkishnermodel_en_5.5.0_3.0_1725822040381.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("turkishnermodel","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("turkishnermodel", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|turkishnermodel|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|412.3 MB|
+
+## References
+
+https://huggingface.co/MesutAktas/TurkishNERModel
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-turkishnermodel_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-turkishnermodel_pipeline_en.md
new file mode 100644
index 00000000000000..2af7ba40d03991
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-turkishnermodel_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English turkishnermodel_pipeline pipeline BertForTokenClassification from MesutAktas
+author: John Snow Labs
+name: turkishnermodel_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkishnermodel_pipeline` is a English model originally trained by MesutAktas.
+
+{:.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/turkishnermodel_pipeline_en_5.5.0_3.0_1725822060953.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkishnermodel_pipeline_en_5.5.0_3.0_1725822060953.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
+
+pipeline = PretrainedPipeline("turkishnermodel_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("turkishnermodel_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|turkishnermodel_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|412.3 MB|
+
+## References
+
+https://huggingface.co/MesutAktas/TurkishNERModel
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-tweet_sentiments_analysis_roberta_uholodala_en.md b/docs/_posts/ahmedlone127/2024-09-08-tweet_sentiments_analysis_roberta_uholodala_en.md
new file mode 100644
index 00000000000000..82e37ac09728eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-tweet_sentiments_analysis_roberta_uholodala_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English tweet_sentiments_analysis_roberta_uholodala RoBertaForSequenceClassification from UholoDala
+author: John Snow Labs
+name: tweet_sentiments_analysis_roberta_uholodala
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tweet_sentiments_analysis_roberta_uholodala` is a English model originally trained by UholoDala.
+
+{:.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/tweet_sentiments_analysis_roberta_uholodala_en_5.5.0_3.0_1725830533497.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tweet_sentiments_analysis_roberta_uholodala_en_5.5.0_3.0_1725830533497.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("tweet_sentiments_analysis_roberta_uholodala","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("tweet_sentiments_analysis_roberta_uholodala", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tweet_sentiments_analysis_roberta_uholodala|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|436.4 MB|
+
+## References
+
+https://huggingface.co/UholoDala/tweet_sentiments_analysis_roberta
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-tweet_sentiments_analysis_roberta_uholodala_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-tweet_sentiments_analysis_roberta_uholodala_pipeline_en.md
new file mode 100644
index 00000000000000..da3f8e4344542c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-tweet_sentiments_analysis_roberta_uholodala_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English tweet_sentiments_analysis_roberta_uholodala_pipeline pipeline RoBertaForSequenceClassification from UholoDala
+author: John Snow Labs
+name: tweet_sentiments_analysis_roberta_uholodala_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tweet_sentiments_analysis_roberta_uholodala_pipeline` is a English model originally trained by UholoDala.
+
+{:.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/tweet_sentiments_analysis_roberta_uholodala_pipeline_en_5.5.0_3.0_1725830568378.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tweet_sentiments_analysis_roberta_uholodala_pipeline_en_5.5.0_3.0_1725830568378.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
+
+pipeline = PretrainedPipeline("tweet_sentiments_analysis_roberta_uholodala_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tweet_sentiments_analysis_roberta_uholodala_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tweet_sentiments_analysis_roberta_uholodala_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|436.4 MB|
+
+## References
+
+https://huggingface.co/UholoDala/tweet_sentiments_analysis_roberta
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-tweetrobertanewdataset_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-tweetrobertanewdataset_pipeline_en.md
new file mode 100644
index 00000000000000..4ea7df7e6a5f6c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-tweetrobertanewdataset_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English tweetrobertanewdataset_pipeline pipeline RoBertaForSequenceClassification from AndreiUrsu
+author: John Snow Labs
+name: tweetrobertanewdataset_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tweetrobertanewdataset_pipeline` is a English model originally trained by AndreiUrsu.
+
+{:.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/tweetrobertanewdataset_pipeline_en_5.5.0_3.0_1725820806177.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tweetrobertanewdataset_pipeline_en_5.5.0_3.0_1725820806177.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
+
+pipeline = PretrainedPipeline("tweetrobertanewdataset_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("tweetrobertanewdataset_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tweetrobertanewdataset_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.3 MB|
+
+## References
+
+https://huggingface.co/AndreiUrsu/TweetRobertaNewDataset
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-twitter_roberta_base_emotion_finetuned_wnli_en.md b/docs/_posts/ahmedlone127/2024-09-08-twitter_roberta_base_emotion_finetuned_wnli_en.md
new file mode 100644
index 00000000000000..88da7357d17c63
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-twitter_roberta_base_emotion_finetuned_wnli_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English twitter_roberta_base_emotion_finetuned_wnli RoBertaForSequenceClassification from sujatha2502
+author: John Snow Labs
+name: twitter_roberta_base_emotion_finetuned_wnli
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_base_emotion_finetuned_wnli` is a English model originally trained by sujatha2502.
+
+{:.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/twitter_roberta_base_emotion_finetuned_wnli_en_5.5.0_3.0_1725820682976.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_emotion_finetuned_wnli_en_5.5.0_3.0_1725820682976.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("twitter_roberta_base_emotion_finetuned_wnli","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("twitter_roberta_base_emotion_finetuned_wnli", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_roberta_base_emotion_finetuned_wnli|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|468.1 MB|
+
+## References
+
+https://huggingface.co/sujatha2502/twitter-roberta-base-emotion-finetuned-wnli
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-twitter_roberta_base_emotion_finetuned_wnli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-twitter_roberta_base_emotion_finetuned_wnli_pipeline_en.md
new file mode 100644
index 00000000000000..5d49f3a4714742
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-twitter_roberta_base_emotion_finetuned_wnli_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English twitter_roberta_base_emotion_finetuned_wnli_pipeline pipeline RoBertaForSequenceClassification from sujatha2502
+author: John Snow Labs
+name: twitter_roberta_base_emotion_finetuned_wnli_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_base_emotion_finetuned_wnli_pipeline` is a English model originally trained by sujatha2502.
+
+{:.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/twitter_roberta_base_emotion_finetuned_wnli_pipeline_en_5.5.0_3.0_1725820706752.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_emotion_finetuned_wnli_pipeline_en_5.5.0_3.0_1725820706752.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
+
+pipeline = PretrainedPipeline("twitter_roberta_base_emotion_finetuned_wnli_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("twitter_roberta_base_emotion_finetuned_wnli_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_roberta_base_emotion_finetuned_wnli_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.2 MB|
+
+## References
+
+https://huggingface.co/sujatha2502/twitter-roberta-base-emotion-finetuned-wnli
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-twitter_roberta_base_similarity_latest_en.md b/docs/_posts/ahmedlone127/2024-09-08-twitter_roberta_base_similarity_latest_en.md
new file mode 100644
index 00000000000000..3750fcbd41a884
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-twitter_roberta_base_similarity_latest_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English twitter_roberta_base_similarity_latest RoBertaForSequenceClassification from cardiffnlp
+author: John Snow Labs
+name: twitter_roberta_base_similarity_latest
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_base_similarity_latest` is a English model originally trained by cardiffnlp.
+
+{:.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/twitter_roberta_base_similarity_latest_en_5.5.0_3.0_1725829574934.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_similarity_latest_en_5.5.0_3.0_1725829574934.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("twitter_roberta_base_similarity_latest","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("twitter_roberta_base_similarity_latest", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_roberta_base_similarity_latest|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|468.3 MB|
+
+## References
+
+https://huggingface.co/cardiffnlp/twitter-roberta-base-similarity-latest
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-twitter_roberta_base_similarity_latest_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-twitter_roberta_base_similarity_latest_pipeline_en.md
new file mode 100644
index 00000000000000..48850341087bea
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-twitter_roberta_base_similarity_latest_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English twitter_roberta_base_similarity_latest_pipeline pipeline RoBertaForSequenceClassification from cardiffnlp
+author: John Snow Labs
+name: twitter_roberta_base_similarity_latest_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_base_similarity_latest_pipeline` is a English model originally trained by cardiffnlp.
+
+{:.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/twitter_roberta_base_similarity_latest_pipeline_en_5.5.0_3.0_1725829597643.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_similarity_latest_pipeline_en_5.5.0_3.0_1725829597643.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
+
+pipeline = PretrainedPipeline("twitter_roberta_base_similarity_latest_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("twitter_roberta_base_similarity_latest_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_roberta_base_similarity_latest_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.3 MB|
+
+## References
+
+https://huggingface.co/cardiffnlp/twitter-roberta-base-similarity-latest
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-twitter_roberta_base_topic_latest_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-twitter_roberta_base_topic_latest_pipeline_en.md
new file mode 100644
index 00000000000000..b8649331239c70
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-twitter_roberta_base_topic_latest_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English twitter_roberta_base_topic_latest_pipeline pipeline RoBertaForSequenceClassification from cardiffnlp
+author: John Snow Labs
+name: twitter_roberta_base_topic_latest_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_base_topic_latest_pipeline` is a English model originally trained by cardiffnlp.
+
+{:.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/twitter_roberta_base_topic_latest_pipeline_en_5.5.0_3.0_1725778202501.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_topic_latest_pipeline_en_5.5.0_3.0_1725778202501.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
+
+pipeline = PretrainedPipeline("twitter_roberta_base_topic_latest_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("twitter_roberta_base_topic_latest_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|twitter_roberta_base_topic_latest_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|468.3 MB|
+
+## References
+
+https://huggingface.co/cardiffnlp/twitter-roberta-base-topic-latest
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-uit_cs221_sentiment_analysis_en.md b/docs/_posts/ahmedlone127/2024-09-08-uit_cs221_sentiment_analysis_en.md
new file mode 100644
index 00000000000000..0d1a498eb5c11a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-uit_cs221_sentiment_analysis_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English uit_cs221_sentiment_analysis DistilBertForSequenceClassification from hoangduy0610
+author: John Snow Labs
+name: uit_cs221_sentiment_analysis
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`uit_cs221_sentiment_analysis` is a English model originally trained by hoangduy0610.
+
+{:.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/uit_cs221_sentiment_analysis_en_5.5.0_3.0_1725777252770.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/uit_cs221_sentiment_analysis_en_5.5.0_3.0_1725777252770.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("uit_cs221_sentiment_analysis","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("uit_cs221_sentiment_analysis", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|uit_cs221_sentiment_analysis|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/hoangduy0610/uit-cs221-sentiment-analysis
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-uit_cs221_sentiment_analysis_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-uit_cs221_sentiment_analysis_pipeline_en.md
new file mode 100644
index 00000000000000..92fb7106181103
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-uit_cs221_sentiment_analysis_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English uit_cs221_sentiment_analysis_pipeline pipeline DistilBertForSequenceClassification from hoangduy0610
+author: John Snow Labs
+name: uit_cs221_sentiment_analysis_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`uit_cs221_sentiment_analysis_pipeline` is a English model originally trained by hoangduy0610.
+
+{:.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/uit_cs221_sentiment_analysis_pipeline_en_5.5.0_3.0_1725777263972.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/uit_cs221_sentiment_analysis_pipeline_en_5.5.0_3.0_1725777263972.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
+
+pipeline = PretrainedPipeline("uit_cs221_sentiment_analysis_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("uit_cs221_sentiment_analysis_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|uit_cs221_sentiment_analysis_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/hoangduy0610/uit-cs221-sentiment-analysis
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-umsuka_english_zulu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-umsuka_english_zulu_pipeline_en.md
new file mode 100644
index 00000000000000..c3dcfa8d4a7e18
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-umsuka_english_zulu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English umsuka_english_zulu_pipeline pipeline MarianTransformer from MUNasir
+author: John Snow Labs
+name: umsuka_english_zulu_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`umsuka_english_zulu_pipeline` is a English model originally trained by MUNasir.
+
+{:.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/umsuka_english_zulu_pipeline_en_5.5.0_3.0_1725765908868.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/umsuka_english_zulu_pipeline_en_5.5.0_3.0_1725765908868.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
+
+pipeline = PretrainedPipeline("umsuka_english_zulu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("umsuka_english_zulu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|umsuka_english_zulu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|519.7 MB|
+
+## References
+
+https://huggingface.co/MUNasir/umsuka-en-zu
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-usclm_distilbert_base_uncased_mk1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-usclm_distilbert_base_uncased_mk1_pipeline_en.md
new file mode 100644
index 00000000000000..4211c3a4303302
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-usclm_distilbert_base_uncased_mk1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English usclm_distilbert_base_uncased_mk1_pipeline pipeline DistilBertEmbeddings from hyperdemocracy
+author: John Snow Labs
+name: usclm_distilbert_base_uncased_mk1_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`usclm_distilbert_base_uncased_mk1_pipeline` is a English model originally trained by hyperdemocracy.
+
+{:.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/usclm_distilbert_base_uncased_mk1_pipeline_en_5.5.0_3.0_1725775999667.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/usclm_distilbert_base_uncased_mk1_pipeline_en_5.5.0_3.0_1725775999667.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
+
+pipeline = PretrainedPipeline("usclm_distilbert_base_uncased_mk1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("usclm_distilbert_base_uncased_mk1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|usclm_distilbert_base_uncased_mk1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/hyperdemocracy/usclm-distilbert-base-uncased-mk1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-va_qa_model_en.md b/docs/_posts/ahmedlone127/2024-09-08-va_qa_model_en.md
new file mode 100644
index 00000000000000..9f5e25bbf5253d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-va_qa_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English va_qa_model DistilBertForQuestionAnswering from GuuTran
+author: John Snow Labs
+name: va_qa_model
+date: 2024-09-08
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`va_qa_model` is a English model originally trained by GuuTran.
+
+{:.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/va_qa_model_en_5.5.0_3.0_1725818367051.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/va_qa_model_en_5.5.0_3.0_1725818367051.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("va_qa_model","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("va_qa_model", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|va_qa_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/GuuTran/va_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-vaccine_tweet_sentiments_analysis_model_2_en.md b/docs/_posts/ahmedlone127/2024-09-08-vaccine_tweet_sentiments_analysis_model_2_en.md
new file mode 100644
index 00000000000000..38565e3fd23dba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-vaccine_tweet_sentiments_analysis_model_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vaccine_tweet_sentiments_analysis_model_2 RoBertaForSequenceClassification from Ausbel
+author: John Snow Labs
+name: vaccine_tweet_sentiments_analysis_model_2
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vaccine_tweet_sentiments_analysis_model_2` is a English model originally trained by Ausbel.
+
+{:.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/vaccine_tweet_sentiments_analysis_model_2_en_5.5.0_3.0_1725829658789.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vaccine_tweet_sentiments_analysis_model_2_en_5.5.0_3.0_1725829658789.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = RoBertaForSequenceClassification.pretrained("vaccine_tweet_sentiments_analysis_model_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = RoBertaForSequenceClassification.pretrained("vaccine_tweet_sentiments_analysis_model_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vaccine_tweet_sentiments_analysis_model_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|468.1 MB|
+
+## References
+
+https://huggingface.co/Ausbel/Vaccine-tweet-sentiments-analysis-model-2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-vis_sim_a2a_mpnet_en.md b/docs/_posts/ahmedlone127/2024-09-08-vis_sim_a2a_mpnet_en.md
new file mode 100644
index 00000000000000..d2d1f909c1461b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-vis_sim_a2a_mpnet_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English vis_sim_a2a_mpnet MPNetEmbeddings from edubm
+author: John Snow Labs
+name: vis_sim_a2a_mpnet
+date: 2024-09-08
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`vis_sim_a2a_mpnet` is a English model originally trained by edubm.
+
+{:.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/vis_sim_a2a_mpnet_en_5.5.0_3.0_1725817262276.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vis_sim_a2a_mpnet_en_5.5.0_3.0_1725817262276.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("vis_sim_a2a_mpnet","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("vis_sim_a2a_mpnet","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vis_sim_a2a_mpnet|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|406.7 MB|
+
+## References
+
+https://huggingface.co/edubm/vis-sim-a2a-mpnet
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-w_zh2en_hsk_en.md b/docs/_posts/ahmedlone127/2024-09-08-w_zh2en_hsk_en.md
new file mode 100644
index 00000000000000..6e2112237ee544
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-w_zh2en_hsk_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English w_zh2en_hsk MarianTransformer from Chun
+author: John Snow Labs
+name: w_zh2en_hsk
+date: 2024-09-08
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`w_zh2en_hsk` is a English model originally trained by Chun.
+
+{:.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/w_zh2en_hsk_en_5.5.0_3.0_1725831495781.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/w_zh2en_hsk_en_5.5.0_3.0_1725831495781.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("w_zh2en_hsk","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("w_zh2en_hsk","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|w_zh2en_hsk|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|536.9 MB|
+
+## References
+
+https://huggingface.co/Chun/w-zh2en-hsk
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-w_zh2en_hsk_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-w_zh2en_hsk_pipeline_en.md
new file mode 100644
index 00000000000000..5bd59da17dbdd2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-w_zh2en_hsk_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English w_zh2en_hsk_pipeline pipeline MarianTransformer from Chun
+author: John Snow Labs
+name: w_zh2en_hsk_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`w_zh2en_hsk_pipeline` is a English model originally trained by Chun.
+
+{:.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/w_zh2en_hsk_pipeline_en_5.5.0_3.0_1725831523930.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/w_zh2en_hsk_pipeline_en_5.5.0_3.0_1725831523930.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
+
+pipeline = PretrainedPipeline("w_zh2en_hsk_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("w_zh2en_hsk_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|w_zh2en_hsk_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|537.4 MB|
+
+## References
+
+https://huggingface.co/Chun/w-zh2en-hsk
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-weatherconv_chatbot_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-weatherconv_chatbot_pipeline_en.md
new file mode 100644
index 00000000000000..65c4108e822335
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-weatherconv_chatbot_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English weatherconv_chatbot_pipeline pipeline DistilBertForQuestionAnswering from kbr26
+author: John Snow Labs
+name: weatherconv_chatbot_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`weatherconv_chatbot_pipeline` is a English model originally trained by kbr26.
+
+{:.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/weatherconv_chatbot_pipeline_en_5.5.0_3.0_1725818693351.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/weatherconv_chatbot_pipeline_en_5.5.0_3.0_1725818693351.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
+
+pipeline = PretrainedPipeline("weatherconv_chatbot_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("weatherconv_chatbot_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|weatherconv_chatbot_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/kbr26/weatherConv_chatbot
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-withinapps_ndd_addressbook_test_content_tags_en.md b/docs/_posts/ahmedlone127/2024-09-08-withinapps_ndd_addressbook_test_content_tags_en.md
new file mode 100644
index 00000000000000..8ea874421e99ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-withinapps_ndd_addressbook_test_content_tags_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English withinapps_ndd_addressbook_test_content_tags DistilBertForSequenceClassification from lgk03
+author: John Snow Labs
+name: withinapps_ndd_addressbook_test_content_tags
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, distilbert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`withinapps_ndd_addressbook_test_content_tags` is a English model originally trained by lgk03.
+
+{:.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/withinapps_ndd_addressbook_test_content_tags_en_5.5.0_3.0_1725777554142.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/withinapps_ndd_addressbook_test_content_tags_en_5.5.0_3.0_1725777554142.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DistilBertForSequenceClassification.pretrained("withinapps_ndd_addressbook_test_content_tags","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DistilBertForSequenceClassification.pretrained("withinapps_ndd_addressbook_test_content_tags", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|withinapps_ndd_addressbook_test_content_tags|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lgk03/WITHINAPPS_NDD-addressbook_test-content_tags
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-withinapps_ndd_addressbook_test_content_tags_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-withinapps_ndd_addressbook_test_content_tags_pipeline_en.md
new file mode 100644
index 00000000000000..0ec47c79b3a285
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-withinapps_ndd_addressbook_test_content_tags_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English withinapps_ndd_addressbook_test_content_tags_pipeline pipeline DistilBertForSequenceClassification from lgk03
+author: John Snow Labs
+name: withinapps_ndd_addressbook_test_content_tags_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`withinapps_ndd_addressbook_test_content_tags_pipeline` is a English model originally trained by lgk03.
+
+{:.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/withinapps_ndd_addressbook_test_content_tags_pipeline_en_5.5.0_3.0_1725777565479.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/withinapps_ndd_addressbook_test_content_tags_pipeline_en_5.5.0_3.0_1725777565479.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
+
+pipeline = PretrainedPipeline("withinapps_ndd_addressbook_test_content_tags_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("withinapps_ndd_addressbook_test_content_tags_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|withinapps_ndd_addressbook_test_content_tags_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/lgk03/WITHINAPPS_NDD-addressbook_test-content_tags
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-wnut17_testclassification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-wnut17_testclassification_pipeline_en.md
new file mode 100644
index 00000000000000..32fe6e6c907392
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-wnut17_testclassification_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English wnut17_testclassification_pipeline pipeline DistilBertForTokenClassification from zorb042
+author: John Snow Labs
+name: wnut17_testclassification_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wnut17_testclassification_pipeline` is a English model originally trained by zorb042.
+
+{:.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/wnut17_testclassification_pipeline_en_5.5.0_3.0_1725837632035.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wnut17_testclassification_pipeline_en_5.5.0_3.0_1725837632035.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
+
+pipeline = PretrainedPipeline("wnut17_testclassification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("wnut17_testclassification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|wnut17_testclassification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/zorb042/wnut17_testclassification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-working_en.md b/docs/_posts/ahmedlone127/2024-09-08-working_en.md
new file mode 100644
index 00000000000000..bd39853154a4ce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-working_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English working DistilBertForTokenClassification from Svangorden13
+author: John Snow Labs
+name: working
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`working` is a English model originally trained by Svangorden13.
+
+{:.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/working_en_5.5.0_3.0_1725827533639.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/working_en_5.5.0_3.0_1725827533639.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("working","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("working", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|working|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/Svangorden13/working
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_conll2002_dutch_nl.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_conll2002_dutch_nl.md
new file mode 100644
index 00000000000000..659742f701d39b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_conll2002_dutch_nl.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Dutch, Flemish xlm_roberta_base_conll2002_dutch XlmRoBertaForTokenClassification from wpnbos
+author: John Snow Labs
+name: xlm_roberta_base_conll2002_dutch
+date: 2024-09-08
+tags: [nl, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: nl
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_conll2002_dutch` is a Dutch, Flemish model originally trained by wpnbos.
+
+{:.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/xlm_roberta_base_conll2002_dutch_nl_5.5.0_3.0_1725805979635.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_conll2002_dutch_nl_5.5.0_3.0_1725805979635.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_conll2002_dutch","nl") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_conll2002_dutch", "nl")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_conll2002_dutch|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|nl|
+|Size:|852.0 MB|
+
+## References
+
+https://huggingface.co/wpnbos/xlm-roberta-base-conll2002-dutch
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_conll2002_dutch_pipeline_nl.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_conll2002_dutch_pipeline_nl.md
new file mode 100644
index 00000000000000..9c47f18d48756d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_conll2002_dutch_pipeline_nl.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Dutch, Flemish xlm_roberta_base_conll2002_dutch_pipeline pipeline XlmRoBertaForTokenClassification from wpnbos
+author: John Snow Labs
+name: xlm_roberta_base_conll2002_dutch_pipeline
+date: 2024-09-08
+tags: [nl, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: nl
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_conll2002_dutch_pipeline` is a Dutch, Flemish model originally trained by wpnbos.
+
+{:.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/xlm_roberta_base_conll2002_dutch_pipeline_nl_5.5.0_3.0_1725806044653.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_conll2002_dutch_pipeline_nl_5.5.0_3.0_1725806044653.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_conll2002_dutch_pipeline", lang = "nl")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_conll2002_dutch_pipeline", lang = "nl")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_conll2002_dutch_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|nl|
+|Size:|852.0 MB|
+
+## References
+
+https://huggingface.co/wpnbos/xlm-roberta-base-conll2002-dutch
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_malagasy_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_malagasy_pipeline_en.md
new file mode 100644
index 00000000000000..b6fe085c84c584
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_malagasy_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_malagasy_pipeline pipeline XlmRoBertaEmbeddings from Davlan
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_malagasy_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_malagasy_pipeline` is a English model originally trained by Davlan.
+
+{:.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/xlm_roberta_base_finetuned_malagasy_pipeline_en_5.5.0_3.0_1725770449776.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_malagasy_pipeline_en_5.5.0_3.0_1725770449776.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_malagasy_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_malagasy_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_malagasy_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/Davlan/xlm-roberta-base-finetuned-malagasy
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_marc_english_giannipinelli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_marc_english_giannipinelli_pipeline_en.md
new file mode 100644
index 00000000000000..8c8efdafd0639c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_marc_english_giannipinelli_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_marc_english_giannipinelli_pipeline pipeline XlmRoBertaForSequenceClassification from Giannipinelli
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_marc_english_giannipinelli_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_marc_english_giannipinelli_pipeline` is a English model originally trained by Giannipinelli.
+
+{:.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/xlm_roberta_base_finetuned_marc_english_giannipinelli_pipeline_en_5.5.0_3.0_1725780361141.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_marc_english_giannipinelli_pipeline_en_5.5.0_3.0_1725780361141.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_marc_english_giannipinelli_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_marc_english_giannipinelli_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_marc_english_giannipinelli_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|833.5 MB|
+
+## References
+
+https://huggingface.co/Giannipinelli/xlm-roberta-base-finetuned-marc-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_all_agvelu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_all_agvelu_pipeline_en.md
new file mode 100644
index 00000000000000..4b8ea1132761dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_all_agvelu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_agvelu_pipeline pipeline XlmRoBertaForTokenClassification from agvelu
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_agvelu_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_agvelu_pipeline` is a English model originally trained by agvelu.
+
+{:.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/xlm_roberta_base_finetuned_panx_all_agvelu_pipeline_en_5.5.0_3.0_1725807209695.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_agvelu_pipeline_en_5.5.0_3.0_1725807209695.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_agvelu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_all_agvelu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_agvelu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|858.2 MB|
+
+## References
+
+https://huggingface.co/agvelu/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_all_penguinman73_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_all_penguinman73_en.md
new file mode 100644
index 00000000000000..cc827479c3b797
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_all_penguinman73_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_all_penguinman73 XlmRoBertaForTokenClassification from penguinman73
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_all_penguinman73
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_all_penguinman73` is a English model originally trained by penguinman73.
+
+{:.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/xlm_roberta_base_finetuned_panx_all_penguinman73_en_5.5.0_3.0_1725807380225.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_all_penguinman73_en_5.5.0_3.0_1725807380225.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_penguinman73","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_all_penguinman73", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_all_penguinman73|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|848.0 MB|
+
+## References
+
+https://huggingface.co/penguinman73/xlm-roberta-base-finetuned-panx-all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_english_agvelu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_english_agvelu_pipeline_en.md
new file mode 100644
index 00000000000000..9c11b2a8f274cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_english_agvelu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_agvelu_pipeline pipeline XlmRoBertaForTokenClassification from agvelu
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_agvelu_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_agvelu_pipeline` is a English model originally trained by agvelu.
+
+{:.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/xlm_roberta_base_finetuned_panx_english_agvelu_pipeline_en_5.5.0_3.0_1725783871550.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_agvelu_pipeline_en_5.5.0_3.0_1725783871550.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_agvelu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_agvelu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_agvelu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|826.4 MB|
+
+## References
+
+https://huggingface.co/agvelu/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_english_cyycyy_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_english_cyycyy_pipeline_en.md
new file mode 100644
index 00000000000000..1aaef54f455234
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_english_cyycyy_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_cyycyy_pipeline pipeline XlmRoBertaForTokenClassification from cyycyy
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_cyycyy_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_cyycyy_pipeline` is a English model originally trained by cyycyy.
+
+{:.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/xlm_roberta_base_finetuned_panx_english_cyycyy_pipeline_en_5.5.0_3.0_1725783931748.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_cyycyy_pipeline_en_5.5.0_3.0_1725783931748.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_cyycyy_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_cyycyy_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_cyycyy_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|826.4 MB|
+
+## References
+
+https://huggingface.co/cyycyy/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_english_deepaperi_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_english_deepaperi_en.md
new file mode 100644
index 00000000000000..273f21b8a9cf1c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_english_deepaperi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_deepaperi XlmRoBertaForTokenClassification from DeepaPeri
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_deepaperi
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_deepaperi` is a English model originally trained by DeepaPeri.
+
+{:.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/xlm_roberta_base_finetuned_panx_english_deepaperi_en_5.5.0_3.0_1725806122460.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_deepaperi_en_5.5.0_3.0_1725806122460.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_deepaperi","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_deepaperi", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_deepaperi|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|845.6 MB|
+
+## References
+
+https://huggingface.co/DeepaPeri/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_english_hbtemari_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_english_hbtemari_pipeline_en.md
new file mode 100644
index 00000000000000..38e8f49def1368
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_english_hbtemari_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_hbtemari_pipeline pipeline XlmRoBertaForTokenClassification from HBtemari
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_hbtemari_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_hbtemari_pipeline` is a English model originally trained by HBtemari.
+
+{:.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/xlm_roberta_base_finetuned_panx_english_hbtemari_pipeline_en_5.5.0_3.0_1725807147416.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_hbtemari_pipeline_en_5.5.0_3.0_1725807147416.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_hbtemari_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_hbtemari_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_hbtemari_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|826.4 MB|
+
+## References
+
+https://huggingface.co/HBtemari/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_english_rlpeter70_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_english_rlpeter70_pipeline_en.md
new file mode 100644
index 00000000000000..18b3bec5c007b7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_english_rlpeter70_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_rlpeter70_pipeline pipeline XlmRoBertaForTokenClassification from rlpeter70
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_rlpeter70_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_rlpeter70_pipeline` is a English model originally trained by rlpeter70.
+
+{:.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/xlm_roberta_base_finetuned_panx_english_rlpeter70_pipeline_en_5.5.0_3.0_1725783497404.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_rlpeter70_pipeline_en_5.5.0_3.0_1725783497404.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_rlpeter70_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_rlpeter70_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_rlpeter70_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|826.4 MB|
+
+## References
+
+https://huggingface.co/rlpeter70/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_english_wooseok0303_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_english_wooseok0303_en.md
new file mode 100644
index 00000000000000..577652d84fa795
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_english_wooseok0303_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_wooseok0303 XlmRoBertaForTokenClassification from wooseok0303
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_wooseok0303
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_wooseok0303` is a English model originally trained by wooseok0303.
+
+{:.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/xlm_roberta_base_finetuned_panx_english_wooseok0303_en_5.5.0_3.0_1725806161056.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_wooseok0303_en_5.5.0_3.0_1725806161056.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_wooseok0303","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_wooseok0303", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_wooseok0303|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/wooseok0303/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_english_wooseok0303_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_english_wooseok0303_pipeline_en.md
new file mode 100644
index 00000000000000..77ca06082cad8f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_english_wooseok0303_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_wooseok0303_pipeline pipeline XlmRoBertaForTokenClassification from wooseok0303
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_wooseok0303_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_wooseok0303_pipeline` is a English model originally trained by wooseok0303.
+
+{:.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/xlm_roberta_base_finetuned_panx_english_wooseok0303_pipeline_en_5.5.0_3.0_1725806272011.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_wooseok0303_pipeline_en_5.5.0_3.0_1725806272011.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_wooseok0303_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_wooseok0303_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_wooseok0303_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|814.3 MB|
+
+## References
+
+https://huggingface.co/wooseok0303/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_english_youngbreadho_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_english_youngbreadho_en.md
new file mode 100644
index 00000000000000..4fa4d601905fdf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_english_youngbreadho_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_youngbreadho XlmRoBertaForTokenClassification from youngbreadho
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_youngbreadho
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_youngbreadho` is a English model originally trained by youngbreadho.
+
+{:.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/xlm_roberta_base_finetuned_panx_english_youngbreadho_en_5.5.0_3.0_1725806365257.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_youngbreadho_en_5.5.0_3.0_1725806365257.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_youngbreadho","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_english_youngbreadho", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_youngbreadho|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|825.8 MB|
+
+## References
+
+https://huggingface.co/youngbreadho/xlm-roberta-base-finetuned-panx-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_english_youngbreadho_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_english_youngbreadho_pipeline_en.md
new file mode 100644
index 00000000000000..b592da3a2c5bbe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_english_youngbreadho_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_english_youngbreadho_pipeline pipeline XlmRoBertaForTokenClassification from youngbreadho
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_english_youngbreadho_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_youngbreadho_pipeline` is a English model originally trained by youngbreadho.
+
+{:.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/xlm_roberta_base_finetuned_panx_english_youngbreadho_pipeline_en_5.5.0_3.0_1725806459599.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_youngbreadho_pipeline_en_5.5.0_3.0_1725806459599.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_youngbreadho_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_youngbreadho_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_english_youngbreadho_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|825.8 MB|
+
+## References
+
+https://huggingface.co/youngbreadho/xlm-roberta-base-finetuned-panx-en
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_buruzaemon_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_buruzaemon_en.md
new file mode 100644
index 00000000000000..004c9416e7a912
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_buruzaemon_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_buruzaemon XlmRoBertaForTokenClassification from buruzaemon
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_buruzaemon
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_buruzaemon` is a English model originally trained by buruzaemon.
+
+{:.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/xlm_roberta_base_finetuned_panx_french_buruzaemon_en_5.5.0_3.0_1725806677320.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_buruzaemon_en_5.5.0_3.0_1725806677320.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_buruzaemon","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_buruzaemon", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_buruzaemon|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/buruzaemon/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_buruzaemon_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_buruzaemon_pipeline_en.md
new file mode 100644
index 00000000000000..fc5098b233e37f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_buruzaemon_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_buruzaemon_pipeline pipeline XlmRoBertaForTokenClassification from buruzaemon
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_buruzaemon_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_buruzaemon_pipeline` is a English model originally trained by buruzaemon.
+
+{:.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/xlm_roberta_base_finetuned_panx_french_buruzaemon_pipeline_en_5.5.0_3.0_1725806772601.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_buruzaemon_pipeline_en_5.5.0_3.0_1725806772601.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_buruzaemon_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_buruzaemon_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_buruzaemon_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/buruzaemon/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_gcmsrc_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_gcmsrc_en.md
new file mode 100644
index 00000000000000..7bd0657c65b3c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_gcmsrc_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_gcmsrc XlmRoBertaForTokenClassification from gcmsrc
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_gcmsrc
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_gcmsrc` is a English model originally trained by gcmsrc.
+
+{:.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/xlm_roberta_base_finetuned_panx_french_gcmsrc_en_5.5.0_3.0_1725807522120.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_gcmsrc_en_5.5.0_3.0_1725807522120.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_gcmsrc","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_gcmsrc", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_gcmsrc|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|831.2 MB|
+
+## References
+
+https://huggingface.co/gcmsrc/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_gcmsrc_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_gcmsrc_pipeline_en.md
new file mode 100644
index 00000000000000..75c933cd0d4b58
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_gcmsrc_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_gcmsrc_pipeline pipeline XlmRoBertaForTokenClassification from gcmsrc
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_gcmsrc_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_gcmsrc_pipeline` is a English model originally trained by gcmsrc.
+
+{:.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/xlm_roberta_base_finetuned_panx_french_gcmsrc_pipeline_en_5.5.0_3.0_1725807608130.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_gcmsrc_pipeline_en_5.5.0_3.0_1725807608130.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_gcmsrc_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_gcmsrc_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_gcmsrc_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|831.2 MB|
+
+## References
+
+https://huggingface.co/gcmsrc/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_jjglilleberg_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_jjglilleberg_en.md
new file mode 100644
index 00000000000000..8438637ea98a61
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_jjglilleberg_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_jjglilleberg XlmRoBertaForTokenClassification from jjglilleberg
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_jjglilleberg
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_jjglilleberg` is a English model originally trained by jjglilleberg.
+
+{:.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/xlm_roberta_base_finetuned_panx_french_jjglilleberg_en_5.5.0_3.0_1725805820634.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_jjglilleberg_en_5.5.0_3.0_1725805820634.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_jjglilleberg","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_jjglilleberg", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_jjglilleberg|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|827.9 MB|
+
+## References
+
+https://huggingface.co/jjglilleberg/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_lijingxin_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_lijingxin_en.md
new file mode 100644
index 00000000000000..5f493d04563bb8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_lijingxin_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_lijingxin XlmRoBertaForTokenClassification from lijingxin
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_lijingxin
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_lijingxin` is a English model originally trained by lijingxin.
+
+{:.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/xlm_roberta_base_finetuned_panx_french_lijingxin_en_5.5.0_3.0_1725806872173.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_lijingxin_en_5.5.0_3.0_1725806872173.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_lijingxin","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_lijingxin", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_lijingxin|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.9 MB|
+
+## References
+
+https://huggingface.co/lijingxin/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_lijingxin_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_lijingxin_pipeline_en.md
new file mode 100644
index 00000000000000..ec443e8511ddcb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_lijingxin_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_lijingxin_pipeline pipeline XlmRoBertaForTokenClassification from lijingxin
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_lijingxin_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_lijingxin_pipeline` is a English model originally trained by lijingxin.
+
+{:.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/xlm_roberta_base_finetuned_panx_french_lijingxin_pipeline_en_5.5.0_3.0_1725806953870.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_lijingxin_pipeline_en_5.5.0_3.0_1725806953870.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_lijingxin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_lijingxin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_lijingxin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.9 MB|
+
+## References
+
+https://huggingface.co/lijingxin/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_philosucker_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_philosucker_en.md
new file mode 100644
index 00000000000000..083b55535a691a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_philosucker_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_philosucker XlmRoBertaForTokenClassification from philosucker
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_philosucker
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_philosucker` is a English model originally trained by philosucker.
+
+{:.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/xlm_roberta_base_finetuned_panx_french_philosucker_en_5.5.0_3.0_1725806771706.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_philosucker_en_5.5.0_3.0_1725806771706.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_philosucker","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_philosucker", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_philosucker|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|844.9 MB|
+
+## References
+
+https://huggingface.co/philosucker/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_royam0820_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_royam0820_en.md
new file mode 100644
index 00000000000000..f0a7933fb315ad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_royam0820_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_royam0820 XlmRoBertaForTokenClassification from royam0820
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_royam0820
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_royam0820` is a English model originally trained by royam0820.
+
+{:.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/xlm_roberta_base_finetuned_panx_french_royam0820_en_5.5.0_3.0_1725784289014.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_royam0820_en_5.5.0_3.0_1725784289014.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_royam0820","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_royam0820", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_royam0820|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.9 MB|
+
+## References
+
+https://huggingface.co/royam0820/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_royam0820_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_royam0820_pipeline_en.md
new file mode 100644
index 00000000000000..f7b1ce309236a8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_royam0820_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_royam0820_pipeline pipeline XlmRoBertaForTokenClassification from royam0820
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_royam0820_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_royam0820_pipeline` is a English model originally trained by royam0820.
+
+{:.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/xlm_roberta_base_finetuned_panx_french_royam0820_pipeline_en_5.5.0_3.0_1725784364542.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_royam0820_pipeline_en_5.5.0_3.0_1725784364542.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_royam0820_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_french_royam0820_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_royam0820_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.9 MB|
+
+## References
+
+https://huggingface.co/royam0820/xlm-roberta-base-finetuned-panx-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_yezune_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_yezune_en.md
new file mode 100644
index 00000000000000..ee6e96b9342cc0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_french_yezune_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_french_yezune XlmRoBertaForTokenClassification from yezune
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_french_yezune
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_french_yezune` is a English model originally trained by yezune.
+
+{:.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/xlm_roberta_base_finetuned_panx_french_yezune_en_5.5.0_3.0_1725783683464.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_french_yezune_en_5.5.0_3.0_1725783683464.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_yezune","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_french_yezune", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_french_yezune|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.9 MB|
+
+## References
+
+https://huggingface.co/yezune/xlm-roberta-base-finetuned-panx-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_fernweh23_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_fernweh23_en.md
new file mode 100644
index 00000000000000..98f8499507c840
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_fernweh23_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_fernweh23 XlmRoBertaForTokenClassification from Fernweh23
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_fernweh23
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_fernweh23` is a English model originally trained by Fernweh23.
+
+{:.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/xlm_roberta_base_finetuned_panx_german_fernweh23_en_5.5.0_3.0_1725773567320.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_fernweh23_en_5.5.0_3.0_1725773567320.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_fernweh23","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_fernweh23", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_fernweh23|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/Fernweh23/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_french_buruzaemon_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_french_buruzaemon_en.md
new file mode 100644
index 00000000000000..436a43cb46385b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_french_buruzaemon_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_buruzaemon XlmRoBertaForTokenClassification from buruzaemon
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_buruzaemon
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_buruzaemon` is a English model originally trained by buruzaemon.
+
+{:.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/xlm_roberta_base_finetuned_panx_german_french_buruzaemon_en_5.5.0_3.0_1725772856400.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_buruzaemon_en_5.5.0_3.0_1725772856400.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_buruzaemon","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_buruzaemon", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_buruzaemon|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/buruzaemon/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_french_goldenk_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_french_goldenk_en.md
new file mode 100644
index 00000000000000..1987c523d5f49d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_french_goldenk_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_goldenk XlmRoBertaForTokenClassification from goldenk
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_goldenk
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_goldenk` is a English model originally trained by goldenk.
+
+{:.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/xlm_roberta_base_finetuned_panx_german_french_goldenk_en_5.5.0_3.0_1725785424241.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_goldenk_en_5.5.0_3.0_1725785424241.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_goldenk","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_goldenk", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_goldenk|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|858.2 MB|
+
+## References
+
+https://huggingface.co/goldenk/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_french_goldenk_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_french_goldenk_pipeline_en.md
new file mode 100644
index 00000000000000..d1f11c62350336
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_french_goldenk_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_goldenk_pipeline pipeline XlmRoBertaForTokenClassification from goldenk
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_goldenk_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_goldenk_pipeline` is a English model originally trained by goldenk.
+
+{:.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/xlm_roberta_base_finetuned_panx_german_french_goldenk_pipeline_en_5.5.0_3.0_1725785492529.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_goldenk_pipeline_en_5.5.0_3.0_1725785492529.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_goldenk_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_goldenk_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_goldenk_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|858.2 MB|
+
+## References
+
+https://huggingface.co/goldenk/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_french_huangjia_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_french_huangjia_pipeline_en.md
new file mode 100644
index 00000000000000..f57e0b834f65cd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_french_huangjia_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_huangjia_pipeline pipeline XlmRoBertaForTokenClassification from huangjia
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_huangjia_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_huangjia_pipeline` is a English model originally trained by huangjia.
+
+{:.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/xlm_roberta_base_finetuned_panx_german_french_huangjia_pipeline_en_5.5.0_3.0_1725784945617.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_huangjia_pipeline_en_5.5.0_3.0_1725784945617.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_huangjia_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_huangjia_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_huangjia_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|857.0 MB|
+
+## References
+
+https://huggingface.co/huangjia/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_french_opengl99_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_french_opengl99_en.md
new file mode 100644
index 00000000000000..2da5f87a00acbc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_french_opengl99_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_opengl99 XlmRoBertaForTokenClassification from opengl99
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_opengl99
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_opengl99` is a English model originally trained by opengl99.
+
+{:.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/xlm_roberta_base_finetuned_panx_german_french_opengl99_en_5.5.0_3.0_1725807579709.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_opengl99_en_5.5.0_3.0_1725807579709.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_opengl99","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_opengl99", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_opengl99|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|858.2 MB|
+
+## References
+
+https://huggingface.co/opengl99/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_french_opengl99_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_french_opengl99_pipeline_en.md
new file mode 100644
index 00000000000000..f7921cfcb12a8f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_french_opengl99_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_opengl99_pipeline pipeline XlmRoBertaForTokenClassification from opengl99
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_opengl99_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_opengl99_pipeline` is a English model originally trained by opengl99.
+
+{:.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/xlm_roberta_base_finetuned_panx_german_french_opengl99_pipeline_en_5.5.0_3.0_1725807647405.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_opengl99_pipeline_en_5.5.0_3.0_1725807647405.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_opengl99_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_opengl99_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_opengl99_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|858.2 MB|
+
+## References
+
+https://huggingface.co/opengl99/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_french_skr3178_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_french_skr3178_en.md
new file mode 100644
index 00000000000000..9cc85839de82ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_french_skr3178_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_skr3178 XlmRoBertaForTokenClassification from skr3178
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_skr3178
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_skr3178` is a English model originally trained by skr3178.
+
+{:.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/xlm_roberta_base_finetuned_panx_german_french_skr3178_en_5.5.0_3.0_1725784401772.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_skr3178_en_5.5.0_3.0_1725784401772.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_skr3178","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_skr3178", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_skr3178|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|858.2 MB|
+
+## References
+
+https://huggingface.co/skr3178/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_french_skr3178_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_french_skr3178_pipeline_en.md
new file mode 100644
index 00000000000000..21f241dd057a05
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_french_skr3178_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_skr3178_pipeline pipeline XlmRoBertaForTokenClassification from skr3178
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_skr3178_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_skr3178_pipeline` is a English model originally trained by skr3178.
+
+{:.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/xlm_roberta_base_finetuned_panx_german_french_skr3178_pipeline_en_5.5.0_3.0_1725784463903.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_skr3178_pipeline_en_5.5.0_3.0_1725784463903.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_skr3178_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_skr3178_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_skr3178_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|858.2 MB|
+
+## References
+
+https://huggingface.co/skr3178/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_french_wendao_123_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_french_wendao_123_en.md
new file mode 100644
index 00000000000000..bfbbd2e732a0e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_french_wendao_123_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_wendao_123 XlmRoBertaForTokenClassification from Wendao-123
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_wendao_123
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_wendao_123` is a English model originally trained by Wendao-123.
+
+{:.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/xlm_roberta_base_finetuned_panx_german_french_wendao_123_en_5.5.0_3.0_1725783276988.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_wendao_123_en_5.5.0_3.0_1725783276988.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_wendao_123","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_french_wendao_123", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_wendao_123|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/Wendao-123/xlm-roberta-base-finetuned-panx-de-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_french_wendao_123_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_french_wendao_123_pipeline_en.md
new file mode 100644
index 00000000000000..da0ab15f1d4f04
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_french_wendao_123_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_french_wendao_123_pipeline pipeline XlmRoBertaForTokenClassification from Wendao-123
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_french_wendao_123_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_wendao_123_pipeline` is a English model originally trained by Wendao-123.
+
+{:.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/xlm_roberta_base_finetuned_panx_german_french_wendao_123_pipeline_en_5.5.0_3.0_1725783359818.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_wendao_123_pipeline_en_5.5.0_3.0_1725783359818.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_wendao_123_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_wendao_123_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_french_wendao_123_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|843.4 MB|
+
+## References
+
+https://huggingface.co/Wendao-123/xlm-roberta-base-finetuned-panx-de-fr
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_mlagrand_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_mlagrand_en.md
new file mode 100644
index 00000000000000..205d5c63f7678f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_mlagrand_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_mlagrand XlmRoBertaForTokenClassification from mlagrand
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_mlagrand
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_mlagrand` is a English model originally trained by mlagrand.
+
+{:.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/xlm_roberta_base_finetuned_panx_german_mlagrand_en_5.5.0_3.0_1725772803078.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_mlagrand_en_5.5.0_3.0_1725772803078.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_mlagrand","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_mlagrand", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_mlagrand|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|810.5 MB|
+
+## References
+
+https://huggingface.co/mlagrand/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_mlagrand_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_mlagrand_pipeline_en.md
new file mode 100644
index 00000000000000..8b4ff5bbe7f6f9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_mlagrand_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_mlagrand_pipeline pipeline XlmRoBertaForTokenClassification from mlagrand
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_mlagrand_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_mlagrand_pipeline` is a English model originally trained by mlagrand.
+
+{:.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/xlm_roberta_base_finetuned_panx_german_mlagrand_pipeline_en_5.5.0_3.0_1725772901786.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_mlagrand_pipeline_en_5.5.0_3.0_1725772901786.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_mlagrand_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_mlagrand_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_mlagrand_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|810.5 MB|
+
+## References
+
+https://huggingface.co/mlagrand/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_nitin1690_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_nitin1690_pipeline_en.md
new file mode 100644
index 00000000000000..4b9309ebb860d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_nitin1690_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_nitin1690_pipeline pipeline XlmRoBertaForTokenClassification from nitin1690
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_nitin1690_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_nitin1690_pipeline` is a English model originally trained by nitin1690.
+
+{:.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/xlm_roberta_base_finetuned_panx_german_nitin1690_pipeline_en_5.5.0_3.0_1725773140827.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_nitin1690_pipeline_en_5.5.0_3.0_1725773140827.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_nitin1690_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_nitin1690_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_nitin1690_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|840.8 MB|
+
+## References
+
+https://huggingface.co/nitin1690/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_sbooms_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_sbooms_en.md
new file mode 100644
index 00000000000000..dabd7524760681
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_sbooms_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_sbooms XlmRoBertaForTokenClassification from sbooms
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_sbooms
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_sbooms` is a English model originally trained by sbooms.
+
+{:.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/xlm_roberta_base_finetuned_panx_german_sbooms_en_5.5.0_3.0_1725784286373.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_sbooms_en_5.5.0_3.0_1725784286373.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_sbooms","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_sbooms", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_sbooms|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/sbooms/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_scjones_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_scjones_en.md
new file mode 100644
index 00000000000000..406a4f487625a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_scjones_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_scjones XlmRoBertaForTokenClassification from scjones
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_scjones
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_scjones` is a English model originally trained by scjones.
+
+{:.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/xlm_roberta_base_finetuned_panx_german_scjones_en_5.5.0_3.0_1725783229832.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_scjones_en_5.5.0_3.0_1725783229832.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_scjones","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_scjones", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_scjones|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/scjones/xlm-roberta-base-finetuned-panx-de
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_scjones_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_scjones_pipeline_en.md
new file mode 100644
index 00000000000000..f6fcb3b1753e31
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_german_scjones_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_german_scjones_pipeline pipeline XlmRoBertaForTokenClassification from scjones
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_german_scjones_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_scjones_pipeline` is a English model originally trained by scjones.
+
+{:.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/xlm_roberta_base_finetuned_panx_german_scjones_pipeline_en_5.5.0_3.0_1725783294040.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_scjones_pipeline_en_5.5.0_3.0_1725783294040.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_scjones_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_scjones_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_german_scjones_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/scjones/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_italian_aaa01101312_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_italian_aaa01101312_en.md
new file mode 100644
index 00000000000000..c2f596c4b02dc4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_italian_aaa01101312_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_aaa01101312 XlmRoBertaForTokenClassification from AAA01101312
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_aaa01101312
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_aaa01101312` is a English model originally trained by AAA01101312.
+
+{:.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/xlm_roberta_base_finetuned_panx_italian_aaa01101312_en_5.5.0_3.0_1725774117547.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_aaa01101312_en_5.5.0_3.0_1725774117547.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_aaa01101312","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_aaa01101312", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_aaa01101312|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|816.7 MB|
+
+## References
+
+https://huggingface.co/AAA01101312/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_italian_shinta0615_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_italian_shinta0615_en.md
new file mode 100644
index 00000000000000..a73151c945f98a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_italian_shinta0615_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_shinta0615 XlmRoBertaForTokenClassification from shinta0615
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_shinta0615
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_shinta0615` is a English model originally trained by shinta0615.
+
+{:.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/xlm_roberta_base_finetuned_panx_italian_shinta0615_en_5.5.0_3.0_1725772983037.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_shinta0615_en_5.5.0_3.0_1725772983037.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_shinta0615","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_shinta0615", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_shinta0615|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|828.6 MB|
+
+## References
+
+https://huggingface.co/shinta0615/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_italian_ultimecia_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_italian_ultimecia_en.md
new file mode 100644
index 00000000000000..98680f0a958822
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_italian_ultimecia_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_italian_ultimecia XlmRoBertaForTokenClassification from ultimecia
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_italian_ultimecia
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_italian_ultimecia` is a English model originally trained by ultimecia.
+
+{:.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/xlm_roberta_base_finetuned_panx_italian_ultimecia_en_5.5.0_3.0_1725783302360.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_italian_ultimecia_en_5.5.0_3.0_1725783302360.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_ultimecia","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_italian_ultimecia", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_italian_ultimecia|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|815.0 MB|
+
+## References
+
+https://huggingface.co/ultimecia/xlm-roberta-base-finetuned-panx-it
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_kazakh_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_kazakh_en.md
new file mode 100644
index 00000000000000..b68507e4d955d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_kazakh_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_kazakh XlmRoBertaForTokenClassification from sultokTheF
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_kazakh
+date: 2024-09-08
+tags: [en, open_source, onnx, token_classification, xlm_roberta, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_kazakh` is a English model originally trained by sultokTheF.
+
+{:.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/xlm_roberta_base_finetuned_panx_kazakh_en_5.5.0_3.0_1725774034987.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_kazakh_en_5.5.0_3.0_1725774034987.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_kazakh","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_kazakh", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_kazakh|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|822.5 MB|
+
+## References
+
+https://huggingface.co/sultokTheF/xlm-roberta-base-finetuned-panx-kk
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_kazakh_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_kazakh_pipeline_en.md
new file mode 100644
index 00000000000000..e02c121bc32e2b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_finetuned_panx_kazakh_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_finetuned_panx_kazakh_pipeline pipeline XlmRoBertaForTokenClassification from sultokTheF
+author: John Snow Labs
+name: xlm_roberta_base_finetuned_panx_kazakh_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_kazakh_pipeline` is a English model originally trained by sultokTheF.
+
+{:.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/xlm_roberta_base_finetuned_panx_kazakh_pipeline_en_5.5.0_3.0_1725774125302.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_kazakh_pipeline_en_5.5.0_3.0_1725774125302.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_kazakh_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_kazakh_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_finetuned_panx_kazakh_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|822.5 MB|
+
+## References
+
+https://huggingface.co/sultokTheF/xlm-roberta-base-finetuned-panx-kk
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_lcc_english_persian_farsi_2e_5_42_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_lcc_english_persian_farsi_2e_5_42_en.md
new file mode 100644
index 00000000000000..48f8a40f2ea227
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_lcc_english_persian_farsi_2e_5_42_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_lcc_english_persian_farsi_2e_5_42 XlmRoBertaForSequenceClassification from EhsanAghazadeh
+author: John Snow Labs
+name: xlm_roberta_base_lcc_english_persian_farsi_2e_5_42
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_lcc_english_persian_farsi_2e_5_42` is a English model originally trained by EhsanAghazadeh.
+
+{:.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/xlm_roberta_base_lcc_english_persian_farsi_2e_5_42_en_5.5.0_3.0_1725799419236.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lcc_english_persian_farsi_2e_5_42_en_5.5.0_3.0_1725799419236.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_lcc_english_persian_farsi_2e_5_42","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_lcc_english_persian_farsi_2e_5_42", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_lcc_english_persian_farsi_2e_5_42|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|818.6 MB|
+
+## References
+
+https://huggingface.co/EhsanAghazadeh/xlm-roberta-base-lcc-en-fa-2e-5-42
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_russian_sentiment_rureviews_pipeline_ru.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_russian_sentiment_rureviews_pipeline_ru.md
new file mode 100644
index 00000000000000..42ed9c27111263
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_russian_sentiment_rureviews_pipeline_ru.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Russian xlm_roberta_base_russian_sentiment_rureviews_pipeline pipeline XlmRoBertaForSequenceClassification from sismetanin
+author: John Snow Labs
+name: xlm_roberta_base_russian_sentiment_rureviews_pipeline
+date: 2024-09-08
+tags: [ru, open_source, pipeline, onnx]
+task: Text Classification
+language: ru
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_russian_sentiment_rureviews_pipeline` is a Russian model originally trained by sismetanin.
+
+{:.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/xlm_roberta_base_russian_sentiment_rureviews_pipeline_ru_5.5.0_3.0_1725781439758.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_russian_sentiment_rureviews_pipeline_ru_5.5.0_3.0_1725781439758.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_russian_sentiment_rureviews_pipeline", lang = "ru")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_russian_sentiment_rureviews_pipeline", lang = "ru")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_russian_sentiment_rureviews_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ru|
+|Size:|794.9 MB|
+
+## References
+
+https://huggingface.co/sismetanin/xlm_roberta_base-ru-sentiment-rureviews
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_russian_sentiment_rureviews_ru.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_russian_sentiment_rureviews_ru.md
new file mode 100644
index 00000000000000..bcfb4afa3c9647
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_russian_sentiment_rureviews_ru.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Russian xlm_roberta_base_russian_sentiment_rureviews XlmRoBertaForSequenceClassification from sismetanin
+author: John Snow Labs
+name: xlm_roberta_base_russian_sentiment_rureviews
+date: 2024-09-08
+tags: [ru, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: ru
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_russian_sentiment_rureviews` is a Russian model originally trained by sismetanin.
+
+{:.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/xlm_roberta_base_russian_sentiment_rureviews_ru_5.5.0_3.0_1725781309151.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_russian_sentiment_rureviews_ru_5.5.0_3.0_1725781309151.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_russian_sentiment_rureviews","ru") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_russian_sentiment_rureviews", "ru")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_russian_sentiment_rureviews|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|ru|
+|Size:|794.9 MB|
+
+## References
+
+https://huggingface.co/sismetanin/xlm_roberta_base-ru-sentiment-rureviews
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_seed42_original_esp_kinyarwanda_eng_train_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_seed42_original_esp_kinyarwanda_eng_train_en.md
new file mode 100644
index 00000000000000..9f88cbb076f07a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_seed42_original_esp_kinyarwanda_eng_train_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_seed42_original_esp_kinyarwanda_eng_train XlmRoBertaForSequenceClassification from shanhy
+author: John Snow Labs
+name: xlm_roberta_base_seed42_original_esp_kinyarwanda_eng_train
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_seed42_original_esp_kinyarwanda_eng_train` is a English model originally trained by shanhy.
+
+{:.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/xlm_roberta_base_seed42_original_esp_kinyarwanda_eng_train_en_5.5.0_3.0_1725779988949.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_seed42_original_esp_kinyarwanda_eng_train_en_5.5.0_3.0_1725779988949.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_seed42_original_esp_kinyarwanda_eng_train","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_seed42_original_esp_kinyarwanda_eng_train", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_seed42_original_esp_kinyarwanda_eng_train|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|802.7 MB|
+
+## References
+
+https://huggingface.co/shanhy/xlm-roberta-base_seed42_original_esp-kin-eng_train
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_seed42_original_esp_kinyarwanda_eng_train_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_seed42_original_esp_kinyarwanda_eng_train_pipeline_en.md
new file mode 100644
index 00000000000000..c260d0acee5db7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_base_seed42_original_esp_kinyarwanda_eng_train_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_seed42_original_esp_kinyarwanda_eng_train_pipeline pipeline XlmRoBertaForSequenceClassification from shanhy
+author: John Snow Labs
+name: xlm_roberta_base_seed42_original_esp_kinyarwanda_eng_train_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_seed42_original_esp_kinyarwanda_eng_train_pipeline` is a English model originally trained by shanhy.
+
+{:.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/xlm_roberta_base_seed42_original_esp_kinyarwanda_eng_train_pipeline_en_5.5.0_3.0_1725780114433.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_seed42_original_esp_kinyarwanda_eng_train_pipeline_en_5.5.0_3.0_1725780114433.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_seed42_original_esp_kinyarwanda_eng_train_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_seed42_original_esp_kinyarwanda_eng_train_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_seed42_original_esp_kinyarwanda_eng_train_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|802.7 MB|
+
+## References
+
+https://huggingface.co/shanhy/xlm-roberta-base_seed42_original_esp-kin-eng_train
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_longformer_base_4096_xnli_french_3_classes_rua_wl_3_classes_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_longformer_base_4096_xnli_french_3_classes_rua_wl_3_classes_pipeline_fr.md
new file mode 100644
index 00000000000000..c9714941c19a64
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_longformer_base_4096_xnli_french_3_classes_rua_wl_3_classes_pipeline_fr.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: French xlm_roberta_longformer_base_4096_xnli_french_3_classes_rua_wl_3_classes_pipeline pipeline XlmRoBertaForSequenceClassification from waboucay
+author: John Snow Labs
+name: xlm_roberta_longformer_base_4096_xnli_french_3_classes_rua_wl_3_classes_pipeline
+date: 2024-09-08
+tags: [fr, open_source, pipeline, onnx]
+task: Text Classification
+language: fr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_longformer_base_4096_xnli_french_3_classes_rua_wl_3_classes_pipeline` is a French model originally trained by waboucay.
+
+{:.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/xlm_roberta_longformer_base_4096_xnli_french_3_classes_rua_wl_3_classes_pipeline_fr_5.5.0_3.0_1725781134893.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_longformer_base_4096_xnli_french_3_classes_rua_wl_3_classes_pipeline_fr_5.5.0_3.0_1725781134893.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
+
+pipeline = PretrainedPipeline("xlm_roberta_longformer_base_4096_xnli_french_3_classes_rua_wl_3_classes_pipeline", lang = "fr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_longformer_base_4096_xnli_french_3_classes_rua_wl_3_classes_pipeline", lang = "fr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_longformer_base_4096_xnli_french_3_classes_rua_wl_3_classes_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|fr|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/waboucay/xlm-roberta-longformer-base-4096-xnli_fr_3_classes-rua_wl_3_classes
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_quran_qa_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_quran_qa_squad_pipeline_en.md
new file mode 100644
index 00000000000000..c39ca12fe56932
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_quran_qa_squad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English xlm_roberta_quran_qa_squad_pipeline pipeline RoBertaForQuestionAnswering from dikyrest
+author: John Snow Labs
+name: xlm_roberta_quran_qa_squad_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_quran_qa_squad_pipeline` is a English model originally trained by dikyrest.
+
+{:.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/xlm_roberta_quran_qa_squad_pipeline_en_5.5.0_3.0_1725833203238.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_quran_qa_squad_pipeline_en_5.5.0_3.0_1725833203238.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
+
+pipeline = PretrainedPipeline("xlm_roberta_quran_qa_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_quran_qa_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_quran_qa_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.6 MB|
+
+## References
+
+https://huggingface.co/dikyrest/xlm-roberta-quran-qa-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_sentiment_romanurdu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_sentiment_romanurdu_pipeline_en.md
new file mode 100644
index 00000000000000..0b21c606d78cb6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlm_roberta_sentiment_romanurdu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_sentiment_romanurdu_pipeline pipeline XlmRoBertaForSequenceClassification from HowMannyMore
+author: John Snow Labs
+name: xlm_roberta_sentiment_romanurdu_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_sentiment_romanurdu_pipeline` is a English model originally trained by HowMannyMore.
+
+{:.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/xlm_roberta_sentiment_romanurdu_pipeline_en_5.5.0_3.0_1725779961646.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_sentiment_romanurdu_pipeline_en_5.5.0_3.0_1725779961646.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
+
+pipeline = PretrainedPipeline("xlm_roberta_sentiment_romanurdu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_sentiment_romanurdu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_sentiment_romanurdu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.0 GB|
+
+## References
+
+https://huggingface.co/HowMannyMore/xlm-roberta-sentiment-romanurdu
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlmr_base_trained_panx_japanese_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-xlmr_base_trained_panx_japanese_pipeline_en.md
new file mode 100644
index 00000000000000..a8313ecfd3bca2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlmr_base_trained_panx_japanese_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlmr_base_trained_panx_japanese_pipeline pipeline XlmRoBertaForTokenClassification from DeepaPeri
+author: John Snow Labs
+name: xlmr_base_trained_panx_japanese_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmr_base_trained_panx_japanese_pipeline` is a English model originally trained by DeepaPeri.
+
+{:.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/xlmr_base_trained_panx_japanese_pipeline_en_5.5.0_3.0_1725784149691.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmr_base_trained_panx_japanese_pipeline_en_5.5.0_3.0_1725784149691.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
+
+pipeline = PretrainedPipeline("xlmr_base_trained_panx_japanese_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmr_base_trained_panx_japanese_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmr_base_trained_panx_japanese_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|789.7 MB|
+
+## References
+
+https://huggingface.co/DeepaPeri/XLMR-BASE-TRAINED-PANX-ja
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlmroberta_ner_gbennett_base_finetuned_panx_de.md b/docs/_posts/ahmedlone127/2024-09-08-xlmroberta_ner_gbennett_base_finetuned_panx_de.md
new file mode 100644
index 00000000000000..57cb9347443abf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlmroberta_ner_gbennett_base_finetuned_panx_de.md
@@ -0,0 +1,113 @@
+---
+layout: model
+title: German XLMRobertaForTokenClassification Base Cased model (from gbennett)
+author: John Snow Labs
+name: xlmroberta_ner_gbennett_base_finetuned_panx
+date: 2024-09-08
+tags: [de, open_source, xlm_roberta, ner, onnx]
+task: Named Entity Recognition
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XLMRobertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `xlm-roberta-base-finetuned-panx-de` is a German model originally trained by `gbennett`.
+
+## Predicted Entities
+
+`PER`, `LOC`, `ORG`
+
+{:.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/xlmroberta_ner_gbennett_base_finetuned_panx_de_5.5.0_3.0_1725774437617.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_gbennett_base_finetuned_panx_de_5.5.0_3.0_1725774437617.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
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+
+token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_gbennett_base_finetuned_panx","de") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("ner")
+
+ner_converter = NerConverter()\
+    .setInputCols(["document", "token", "ner"])\
+    .setOutputCol("ner_chunk")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler()
+      .setInputCols(Array("text"))
+      .setOutputCols(Array("document"))
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val token_classifier = XlmRoBertaForTokenClassification.pretrained("xlmroberta_ner_gbennett_base_finetuned_panx","de")
+    .setInputCols(Array("document", "token"))
+    .setOutputCol("ner")
+
+val ner_converter = new NerConverter()
+    .setInputCols(Array("document", "token', "ner"))
+    .setOutputCol("ner_chunk")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, token_classifier, ner_converter))
+
+val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("de.ner.xlmr_roberta.xtreme.base_finetuned.by_gbennett").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_gbennett_base_finetuned_panx|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|de|
+|Size:|853.8 MB|
+
+## References
+
+References
+
+- https://huggingface.co/gbennett/xlm-roberta-base-finetuned-panx-de
+- https://paperswithcode.com/sota?task=Token+Classification&dataset=xtreme
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlmroberta_ner_gbennett_base_finetuned_panx_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-08-xlmroberta_ner_gbennett_base_finetuned_panx_pipeline_de.md
new file mode 100644
index 00000000000000..e753a8105751e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlmroberta_ner_gbennett_base_finetuned_panx_pipeline_de.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: German xlmroberta_ner_gbennett_base_finetuned_panx_pipeline pipeline XlmRoBertaForTokenClassification from gbennett
+author: John Snow Labs
+name: xlmroberta_ner_gbennett_base_finetuned_panx_pipeline
+date: 2024-09-08
+tags: [de, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_gbennett_base_finetuned_panx_pipeline` is a German model originally trained by gbennett.
+
+{:.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/xlmroberta_ner_gbennett_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725774503314.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_gbennett_base_finetuned_panx_pipeline_de_5.5.0_3.0_1725774503314.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
+
+pipeline = PretrainedPipeline("xlmroberta_ner_gbennett_base_finetuned_panx_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_gbennett_base_finetuned_panx_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_gbennett_base_finetuned_panx_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|853.8 MB|
+
+## References
+
+https://huggingface.co/gbennett/xlm-roberta-base-finetuned-panx-de
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xlmroberta_ner_v3rx2000_base_finetuned_panx_all_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-08-xlmroberta_ner_v3rx2000_base_finetuned_panx_all_pipeline_xx.md
new file mode 100644
index 00000000000000..74b326e57eeb7f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xlmroberta_ner_v3rx2000_base_finetuned_panx_all_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual xlmroberta_ner_v3rx2000_base_finetuned_panx_all_pipeline pipeline XlmRoBertaForTokenClassification from V3RX2000
+author: John Snow Labs
+name: xlmroberta_ner_v3rx2000_base_finetuned_panx_all_pipeline
+date: 2024-09-08
+tags: [xx, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlmroberta_ner_v3rx2000_base_finetuned_panx_all_pipeline` is a Multilingual model originally trained by V3RX2000.
+
+{:.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/xlmroberta_ner_v3rx2000_base_finetuned_panx_all_pipeline_xx_5.5.0_3.0_1725806572920.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlmroberta_ner_v3rx2000_base_finetuned_panx_all_pipeline_xx_5.5.0_3.0_1725806572920.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
+
+pipeline = PretrainedPipeline("xlmroberta_ner_v3rx2000_base_finetuned_panx_all_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlmroberta_ner_v3rx2000_base_finetuned_panx_all_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlmroberta_ner_v3rx2000_base_finetuned_panx_all_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|861.0 MB|
+
+## References
+
+https://huggingface.co/V3RX2000/xlm-roberta-base-finetuned-panx-all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-xtremedistil_l6_h256_uncased_en.md b/docs/_posts/ahmedlone127/2024-09-08-xtremedistil_l6_h256_uncased_en.md
new file mode 100644
index 00000000000000..5356897b4071e1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-xtremedistil_l6_h256_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xtremedistil_l6_h256_uncased BertForSequenceClassification from microsoft
+author: John Snow Labs
+name: xtremedistil_l6_h256_uncased
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xtremedistil_l6_h256_uncased` is a English model originally trained by microsoft.
+
+{:.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/xtremedistil_l6_h256_uncased_en_5.5.0_3.0_1725801952265.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xtremedistil_l6_h256_uncased_en_5.5.0_3.0_1725801952265.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("xtremedistil_l6_h256_uncased","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("xtremedistil_l6_h256_uncased", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xtremedistil_l6_h256_uncased|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|47.3 MB|
+
+## References
+
+https://huggingface.co/microsoft/xtremedistil-l6-h256-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-yelp_polarity_microsoft_deberta_v3_large_seed_2_en.md b/docs/_posts/ahmedlone127/2024-09-08-yelp_polarity_microsoft_deberta_v3_large_seed_2_en.md
new file mode 100644
index 00000000000000..ecc1a98c875800
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-yelp_polarity_microsoft_deberta_v3_large_seed_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English yelp_polarity_microsoft_deberta_v3_large_seed_2 DeBertaForSequenceClassification from utahnlp
+author: John Snow Labs
+name: yelp_polarity_microsoft_deberta_v3_large_seed_2
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yelp_polarity_microsoft_deberta_v3_large_seed_2` is a English model originally trained by utahnlp.
+
+{:.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/yelp_polarity_microsoft_deberta_v3_large_seed_2_en_5.5.0_3.0_1725804096774.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yelp_polarity_microsoft_deberta_v3_large_seed_2_en_5.5.0_3.0_1725804096774.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("yelp_polarity_microsoft_deberta_v3_large_seed_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("yelp_polarity_microsoft_deberta_v3_large_seed_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|yelp_polarity_microsoft_deberta_v3_large_seed_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/utahnlp/yelp_polarity_microsoft_deberta-v3-large_seed-2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-yelp_polarity_microsoft_deberta_v3_large_seed_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-yelp_polarity_microsoft_deberta_v3_large_seed_2_pipeline_en.md
new file mode 100644
index 00000000000000..02550f171de3b9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-yelp_polarity_microsoft_deberta_v3_large_seed_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English yelp_polarity_microsoft_deberta_v3_large_seed_2_pipeline pipeline DeBertaForSequenceClassification from utahnlp
+author: John Snow Labs
+name: yelp_polarity_microsoft_deberta_v3_large_seed_2_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yelp_polarity_microsoft_deberta_v3_large_seed_2_pipeline` is a English model originally trained by utahnlp.
+
+{:.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/yelp_polarity_microsoft_deberta_v3_large_seed_2_pipeline_en_5.5.0_3.0_1725804186185.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yelp_polarity_microsoft_deberta_v3_large_seed_2_pipeline_en_5.5.0_3.0_1725804186185.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
+
+pipeline = PretrainedPipeline("yelp_polarity_microsoft_deberta_v3_large_seed_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("yelp_polarity_microsoft_deberta_v3_large_seed_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|yelp_polarity_microsoft_deberta_v3_large_seed_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/utahnlp/yelp_polarity_microsoft_deberta-v3-large_seed-2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-yelp_polarity_microsoft_deberta_v3_large_seed_3_en.md b/docs/_posts/ahmedlone127/2024-09-08-yelp_polarity_microsoft_deberta_v3_large_seed_3_en.md
new file mode 100644
index 00000000000000..cb7084d3fcd9be
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-yelp_polarity_microsoft_deberta_v3_large_seed_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English yelp_polarity_microsoft_deberta_v3_large_seed_3 DeBertaForSequenceClassification from utahnlp
+author: John Snow Labs
+name: yelp_polarity_microsoft_deberta_v3_large_seed_3
+date: 2024-09-08
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yelp_polarity_microsoft_deberta_v3_large_seed_3` is a English model originally trained by utahnlp.
+
+{:.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/yelp_polarity_microsoft_deberta_v3_large_seed_3_en_5.5.0_3.0_1725804281691.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yelp_polarity_microsoft_deberta_v3_large_seed_3_en_5.5.0_3.0_1725804281691.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("yelp_polarity_microsoft_deberta_v3_large_seed_3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("yelp_polarity_microsoft_deberta_v3_large_seed_3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|yelp_polarity_microsoft_deberta_v3_large_seed_3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/utahnlp/yelp_polarity_microsoft_deberta-v3-large_seed-3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-08-yelp_polarity_microsoft_deberta_v3_large_seed_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-08-yelp_polarity_microsoft_deberta_v3_large_seed_3_pipeline_en.md
new file mode 100644
index 00000000000000..9557b244fc9817
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-08-yelp_polarity_microsoft_deberta_v3_large_seed_3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English yelp_polarity_microsoft_deberta_v3_large_seed_3_pipeline pipeline DeBertaForSequenceClassification from utahnlp
+author: John Snow Labs
+name: yelp_polarity_microsoft_deberta_v3_large_seed_3_pipeline
+date: 2024-09-08
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yelp_polarity_microsoft_deberta_v3_large_seed_3_pipeline` is a English model originally trained by utahnlp.
+
+{:.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/yelp_polarity_microsoft_deberta_v3_large_seed_3_pipeline_en_5.5.0_3.0_1725804371980.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yelp_polarity_microsoft_deberta_v3_large_seed_3_pipeline_en_5.5.0_3.0_1725804371980.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
+
+pipeline = PretrainedPipeline("yelp_polarity_microsoft_deberta_v3_large_seed_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("yelp_polarity_microsoft_deberta_v3_large_seed_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|yelp_polarity_microsoft_deberta_v3_large_seed_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/utahnlp/yelp_polarity_microsoft_deberta-v3-large_seed-3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-007_microsoft_deberta_v3_base_finetuned_yahoo_80_20k_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-007_microsoft_deberta_v3_base_finetuned_yahoo_80_20k_pipeline_en.md
new file mode 100644
index 00000000000000..63436f25ecf4f4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-007_microsoft_deberta_v3_base_finetuned_yahoo_80_20k_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English 007_microsoft_deberta_v3_base_finetuned_yahoo_80_20k_pipeline pipeline DeBertaForSequenceClassification from diogopaes10
+author: John Snow Labs
+name: 007_microsoft_deberta_v3_base_finetuned_yahoo_80_20k_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`007_microsoft_deberta_v3_base_finetuned_yahoo_80_20k_pipeline` is a English model originally trained by diogopaes10.
+
+{:.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/007_microsoft_deberta_v3_base_finetuned_yahoo_80_20k_pipeline_en_5.5.0_3.0_1725879489638.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/007_microsoft_deberta_v3_base_finetuned_yahoo_80_20k_pipeline_en_5.5.0_3.0_1725879489638.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
+
+pipeline = PretrainedPipeline("007_microsoft_deberta_v3_base_finetuned_yahoo_80_20k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("007_microsoft_deberta_v3_base_finetuned_yahoo_80_20k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|007_microsoft_deberta_v3_base_finetuned_yahoo_80_20k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|663.0 MB|
+
+## References
+
+https://huggingface.co/diogopaes10/007-microsoft-deberta-v3-base-finetuned-yahoo-80_20k
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-albert_irony_en.md b/docs/_posts/ahmedlone127/2024-09-09-albert_irony_en.md
new file mode 100644
index 00000000000000..92d166a6b999be
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-albert_irony_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English albert_irony AlbertForSequenceClassification from lilyray
+author: John Snow Labs
+name: albert_irony
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_irony` is a English model originally trained by lilyray.
+
+{:.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/albert_irony_en_5.5.0_3.0_1725889047325.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_irony_en_5.5.0_3.0_1725889047325.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("albert_irony","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("albert_irony", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|albert_irony|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|44.2 MB|
+
+## References
+
+https://huggingface.co/lilyray/albert_irony
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-all_mpnet_base_v2_margin_1_epoch_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-all_mpnet_base_v2_margin_1_epoch_1_pipeline_en.md
new file mode 100644
index 00000000000000..f657466019f588
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-all_mpnet_base_v2_margin_1_epoch_1_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English all_mpnet_base_v2_margin_1_epoch_1_pipeline pipeline MPNetEmbeddings from luiz-and-robert-thesis
+author: John Snow Labs
+name: all_mpnet_base_v2_margin_1_epoch_1_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_margin_1_epoch_1_pipeline` is a English model originally trained by luiz-and-robert-thesis.
+
+{:.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/all_mpnet_base_v2_margin_1_epoch_1_pipeline_en_5.5.0_3.0_1725874925187.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_margin_1_epoch_1_pipeline_en_5.5.0_3.0_1725874925187.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
+
+pipeline = PretrainedPipeline("all_mpnet_base_v2_margin_1_epoch_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("all_mpnet_base_v2_margin_1_epoch_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|all_mpnet_base_v2_margin_1_epoch_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/luiz-and-robert-thesis/all-mpnet-base-v2-margin-1-epoch-1
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-arabic_offensive_comment_model_en.md b/docs/_posts/ahmedlone127/2024-09-09-arabic_offensive_comment_model_en.md
new file mode 100644
index 00000000000000..1ade5849199137
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-arabic_offensive_comment_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English arabic_offensive_comment_model BertForSequenceClassification from nassga
+author: John Snow Labs
+name: arabic_offensive_comment_model
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arabic_offensive_comment_model` is a English model originally trained by nassga.
+
+{:.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/arabic_offensive_comment_model_en_5.5.0_3.0_1725853205283.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arabic_offensive_comment_model_en_5.5.0_3.0_1725853205283.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("arabic_offensive_comment_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("arabic_offensive_comment_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|arabic_offensive_comment_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|507.3 MB|
+
+## References
+
+https://huggingface.co/nassga/arabic-offensive-comment-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-arabic_offensive_comment_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-arabic_offensive_comment_model_pipeline_en.md
new file mode 100644
index 00000000000000..84a5a2ed7b094e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-arabic_offensive_comment_model_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English arabic_offensive_comment_model_pipeline pipeline BertForSequenceClassification from nassga
+author: John Snow Labs
+name: arabic_offensive_comment_model_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arabic_offensive_comment_model_pipeline` is a English model originally trained by nassga.
+
+{:.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/arabic_offensive_comment_model_pipeline_en_5.5.0_3.0_1725853229501.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arabic_offensive_comment_model_pipeline_en_5.5.0_3.0_1725853229501.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
+
+pipeline = PretrainedPipeline("arabic_offensive_comment_model_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("arabic_offensive_comment_model_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|arabic_offensive_comment_model_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|507.3 MB|
+
+## References
+
+https://huggingface.co/nassga/arabic-offensive-comment-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-arabicwojood_flatner_ar.md b/docs/_posts/ahmedlone127/2024-09-09-arabicwojood_flatner_ar.md
new file mode 100644
index 00000000000000..8110472e809bec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-arabicwojood_flatner_ar.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Arabic arabicwojood_flatner BertForTokenClassification from SinaLab
+author: John Snow Labs
+name: arabicwojood_flatner
+date: 2024-09-09
+tags: [ar, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arabicwojood_flatner` is a Arabic model originally trained by SinaLab.
+
+{:.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/arabicwojood_flatner_ar_5.5.0_3.0_1725887454030.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arabicwojood_flatner_ar_5.5.0_3.0_1725887454030.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("arabicwojood_flatner","ar") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("arabicwojood_flatner", "ar")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|arabicwojood_flatner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|ar|
+|Size:|502.9 MB|
+
+## References
+
+https://huggingface.co/SinaLab/ArabicWojood-FlatNER
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-araroberta_sanskrit_saskta_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-09-araroberta_sanskrit_saskta_pipeline_ar.md
new file mode 100644
index 00000000000000..080f06bd640107
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-araroberta_sanskrit_saskta_pipeline_ar.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Arabic araroberta_sanskrit_saskta_pipeline pipeline RoBertaEmbeddings from reemalyami
+author: John Snow Labs
+name: araroberta_sanskrit_saskta_pipeline
+date: 2024-09-09
+tags: [ar, open_source, pipeline, onnx]
+task: Embeddings
+language: ar
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`araroberta_sanskrit_saskta_pipeline` is a Arabic model originally trained by reemalyami.
+
+{:.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/araroberta_sanskrit_saskta_pipeline_ar_5.5.0_3.0_1725883347073.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/araroberta_sanskrit_saskta_pipeline_ar_5.5.0_3.0_1725883347073.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
+
+pipeline = PretrainedPipeline("araroberta_sanskrit_saskta_pipeline", lang = "ar")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("araroberta_sanskrit_saskta_pipeline", lang = "ar")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|araroberta_sanskrit_saskta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ar|
+|Size:|471.0 MB|
+
+## References
+
+https://huggingface.co/reemalyami/AraRoBERTa-SA
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-argureviews_aspect_deberta_v1_en.md b/docs/_posts/ahmedlone127/2024-09-09-argureviews_aspect_deberta_v1_en.md
new file mode 100644
index 00000000000000..6cfbb0892151a5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-argureviews_aspect_deberta_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English argureviews_aspect_deberta_v1 DeBertaForSequenceClassification from nihiluis
+author: John Snow Labs
+name: argureviews_aspect_deberta_v1
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`argureviews_aspect_deberta_v1` is a English model originally trained by nihiluis.
+
+{:.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/argureviews_aspect_deberta_v1_en_5.5.0_3.0_1725879736618.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/argureviews_aspect_deberta_v1_en_5.5.0_3.0_1725879736618.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("argureviews_aspect_deberta_v1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("argureviews_aspect_deberta_v1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|argureviews_aspect_deberta_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/nihiluis/argureviews-aspect-deberta_v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-babyberta_aochildes_2_5m_aochildes_french_without_masking_seed3_finetuned_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-babyberta_aochildes_2_5m_aochildes_french_without_masking_seed3_finetuned_squad_pipeline_en.md
new file mode 100644
index 00000000000000..b9e4e5ad096319
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-babyberta_aochildes_2_5m_aochildes_french_without_masking_seed3_finetuned_squad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English babyberta_aochildes_2_5m_aochildes_french_without_masking_seed3_finetuned_squad_pipeline pipeline RoBertaForQuestionAnswering from lielbin
+author: John Snow Labs
+name: babyberta_aochildes_2_5m_aochildes_french_without_masking_seed3_finetuned_squad_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`babyberta_aochildes_2_5m_aochildes_french_without_masking_seed3_finetuned_squad_pipeline` is a English model originally trained by lielbin.
+
+{:.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/babyberta_aochildes_2_5m_aochildes_french_without_masking_seed3_finetuned_squad_pipeline_en_5.5.0_3.0_1725866587771.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/babyberta_aochildes_2_5m_aochildes_french_without_masking_seed3_finetuned_squad_pipeline_en_5.5.0_3.0_1725866587771.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
+
+pipeline = PretrainedPipeline("babyberta_aochildes_2_5m_aochildes_french_without_masking_seed3_finetuned_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("babyberta_aochildes_2_5m_aochildes_french_without_masking_seed3_finetuned_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|babyberta_aochildes_2_5m_aochildes_french_without_masking_seed3_finetuned_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|32.0 MB|
+
+## References
+
+https://huggingface.co/lielbin/BabyBERTa-aochildes_2.5M_aochildes-french-without-Masking-seed3-finetuned-SQuAD
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-babyberta_french1_25m_masking_finetuned_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-babyberta_french1_25m_masking_finetuned_squad_pipeline_en.md
new file mode 100644
index 00000000000000..6661da9f9a8fd0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-babyberta_french1_25m_masking_finetuned_squad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English babyberta_french1_25m_masking_finetuned_squad_pipeline pipeline RoBertaForQuestionAnswering from lielbin
+author: John Snow Labs
+name: babyberta_french1_25m_masking_finetuned_squad_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`babyberta_french1_25m_masking_finetuned_squad_pipeline` is a English model originally trained by lielbin.
+
+{:.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/babyberta_french1_25m_masking_finetuned_squad_pipeline_en_5.5.0_3.0_1725866965836.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/babyberta_french1_25m_masking_finetuned_squad_pipeline_en_5.5.0_3.0_1725866965836.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
+
+pipeline = PretrainedPipeline("babyberta_french1_25m_masking_finetuned_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("babyberta_french1_25m_masking_finetuned_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|babyberta_french1_25m_masking_finetuned_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|31.9 MB|
+
+## References
+
+https://huggingface.co/lielbin/BabyBERTa-french1.25M-Masking-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-babyberta_french_wikipedia_french_masking_finetuned_qasrl_lielbin_en.md b/docs/_posts/ahmedlone127/2024-09-09-babyberta_french_wikipedia_french_masking_finetuned_qasrl_lielbin_en.md
new file mode 100644
index 00000000000000..ff34658f0f1ad8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-babyberta_french_wikipedia_french_masking_finetuned_qasrl_lielbin_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English babyberta_french_wikipedia_french_masking_finetuned_qasrl_lielbin RoBertaForQuestionAnswering from lielbin
+author: John Snow Labs
+name: babyberta_french_wikipedia_french_masking_finetuned_qasrl_lielbin
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`babyberta_french_wikipedia_french_masking_finetuned_qasrl_lielbin` is a English model originally trained by lielbin.
+
+{:.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/babyberta_french_wikipedia_french_masking_finetuned_qasrl_lielbin_en_5.5.0_3.0_1725876008896.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/babyberta_french_wikipedia_french_masking_finetuned_qasrl_lielbin_en_5.5.0_3.0_1725876008896.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("babyberta_french_wikipedia_french_masking_finetuned_qasrl_lielbin","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("babyberta_french_wikipedia_french_masking_finetuned_qasrl_lielbin", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|babyberta_french_wikipedia_french_masking_finetuned_qasrl_lielbin|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|32.0 MB|
+
+## References
+
+https://huggingface.co/lielbin/BabyBERTa_french_wikipedia_french-Masking-finetuned-qasrl
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-babyberta_french_wikipedia_french_masking_finetuned_qasrl_lielbin_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-babyberta_french_wikipedia_french_masking_finetuned_qasrl_lielbin_pipeline_en.md
new file mode 100644
index 00000000000000..5d1f92d1e65073
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-babyberta_french_wikipedia_french_masking_finetuned_qasrl_lielbin_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English babyberta_french_wikipedia_french_masking_finetuned_qasrl_lielbin_pipeline pipeline RoBertaForQuestionAnswering from lielbin
+author: John Snow Labs
+name: babyberta_french_wikipedia_french_masking_finetuned_qasrl_lielbin_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`babyberta_french_wikipedia_french_masking_finetuned_qasrl_lielbin_pipeline` is a English model originally trained by lielbin.
+
+{:.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/babyberta_french_wikipedia_french_masking_finetuned_qasrl_lielbin_pipeline_en_5.5.0_3.0_1725876010754.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/babyberta_french_wikipedia_french_masking_finetuned_qasrl_lielbin_pipeline_en_5.5.0_3.0_1725876010754.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
+
+pipeline = PretrainedPipeline("babyberta_french_wikipedia_french_masking_finetuned_qasrl_lielbin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("babyberta_french_wikipedia_french_masking_finetuned_qasrl_lielbin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|babyberta_french_wikipedia_french_masking_finetuned_qasrl_lielbin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|32.0 MB|
+
+## References
+
+https://huggingface.co/lielbin/BabyBERTa_french_wikipedia_french-Masking-finetuned-qasrl
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-babyberta_wikipedia1_1_25m_wikipedia_french1_25m_without_masking_seed3_finetuned_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-babyberta_wikipedia1_1_25m_wikipedia_french1_25m_without_masking_seed3_finetuned_squad_pipeline_en.md
new file mode 100644
index 00000000000000..b4957278083e41
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-babyberta_wikipedia1_1_25m_wikipedia_french1_25m_without_masking_seed3_finetuned_squad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English babyberta_wikipedia1_1_25m_wikipedia_french1_25m_without_masking_seed3_finetuned_squad_pipeline pipeline RoBertaForQuestionAnswering from lielbin
+author: John Snow Labs
+name: babyberta_wikipedia1_1_25m_wikipedia_french1_25m_without_masking_seed3_finetuned_squad_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`babyberta_wikipedia1_1_25m_wikipedia_french1_25m_without_masking_seed3_finetuned_squad_pipeline` is a English model originally trained by lielbin.
+
+{:.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/babyberta_wikipedia1_1_25m_wikipedia_french1_25m_without_masking_seed3_finetuned_squad_pipeline_en_5.5.0_3.0_1725876187496.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/babyberta_wikipedia1_1_25m_wikipedia_french1_25m_without_masking_seed3_finetuned_squad_pipeline_en_5.5.0_3.0_1725876187496.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
+
+pipeline = PretrainedPipeline("babyberta_wikipedia1_1_25m_wikipedia_french1_25m_without_masking_seed3_finetuned_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("babyberta_wikipedia1_1_25m_wikipedia_french1_25m_without_masking_seed3_finetuned_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|babyberta_wikipedia1_1_25m_wikipedia_french1_25m_without_masking_seed3_finetuned_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|31.9 MB|
+
+## References
+
+https://huggingface.co/lielbin/BabyBERTa-wikipedia1_1.25M_wikipedia_french1.25M-without-Masking-seed3-finetuned-SQuAD
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-babyberta_wikipedia_french_run3_with_masking_finetuned_french_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-babyberta_wikipedia_french_run3_with_masking_finetuned_french_squad_pipeline_en.md
new file mode 100644
index 00000000000000..f459c7adcc8932
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-babyberta_wikipedia_french_run3_with_masking_finetuned_french_squad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English babyberta_wikipedia_french_run3_with_masking_finetuned_french_squad_pipeline pipeline RoBertaForQuestionAnswering from lielbin
+author: John Snow Labs
+name: babyberta_wikipedia_french_run3_with_masking_finetuned_french_squad_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`babyberta_wikipedia_french_run3_with_masking_finetuned_french_squad_pipeline` is a English model originally trained by lielbin.
+
+{:.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/babyberta_wikipedia_french_run3_with_masking_finetuned_french_squad_pipeline_en_5.5.0_3.0_1725876179673.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/babyberta_wikipedia_french_run3_with_masking_finetuned_french_squad_pipeline_en_5.5.0_3.0_1725876179673.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
+
+pipeline = PretrainedPipeline("babyberta_wikipedia_french_run3_with_masking_finetuned_french_squad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("babyberta_wikipedia_french_run3_with_masking_finetuned_french_squad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|babyberta_wikipedia_french_run3_with_masking_finetuned_french_squad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|32.0 MB|
+
+## References
+
+https://huggingface.co/lielbin/BabyBERTa-wikipedia_french-run3-with-Masking-finetuned-french-SQuAD
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-bert_base_multilingual_cased_ner_xx.md b/docs/_posts/ahmedlone127/2024-09-09-bert_base_multilingual_cased_ner_xx.md
new file mode 100644
index 00000000000000..0fc1da898033d8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-bert_base_multilingual_cased_ner_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual bert_base_multilingual_cased_ner BertForTokenClassification from orgcatorg
+author: John Snow Labs
+name: bert_base_multilingual_cased_ner
+date: 2024-09-09
+tags: [xx, open_source, onnx, token_classification, bert, ner]
+task: Named Entity Recognition
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_ner` is a Multilingual model originally trained by orgcatorg.
+
+{:.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/bert_base_multilingual_cased_ner_xx_5.5.0_3.0_1725887092919.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_ner_xx_5.5.0_3.0_1725887092919.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = BertForTokenClassification.pretrained("bert_base_multilingual_cased_ner","xx") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_base_multilingual_cased_ner", "xx")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_base_multilingual_cased_ner|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|xx|
+|Size:|665.1 MB|
+
+## References
+
+https://huggingface.co/orgcatorg/bert-base-multilingual-cased-ner
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-bert_cased_profanity_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-bert_cased_profanity_pipeline_en.md
new file mode 100644
index 00000000000000..8abe29738774df
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-bert_cased_profanity_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English bert_cased_profanity_pipeline pipeline BertForSequenceClassification from SenswiseData
+author: John Snow Labs
+name: bert_cased_profanity_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_cased_profanity_pipeline` is a English model originally trained by SenswiseData.
+
+{:.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/bert_cased_profanity_pipeline_en_5.5.0_3.0_1725853115067.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_cased_profanity_pipeline_en_5.5.0_3.0_1725853115067.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
+
+pipeline = PretrainedPipeline("bert_cased_profanity_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_cased_profanity_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_cased_profanity_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|414.5 MB|
+
+## References
+
+https://huggingface.co/SenswiseData/bert_cased_profanity
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-bert_embeddings_gbert_large_de.md b/docs/_posts/ahmedlone127/2024-09-09-bert_embeddings_gbert_large_de.md
new file mode 100644
index 00000000000000..ab0fa78c6812cf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-bert_embeddings_gbert_large_de.md
@@ -0,0 +1,116 @@
+---
+layout: model
+title: German Bert Embeddings (Large, Cased)
+author: John Snow Labs
+name: bert_embeddings_gbert_large
+date: 2024-09-09
+tags: [bert, embeddings, de, open_source, onnx]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Bert Embeddings model, uploaded to Hugging Face, adapted and imported into Spark NLP. `gbert-large` is a German model orginally trained by `deepset`.
+
+## 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/bert_embeddings_gbert_large_de_5.5.0_3.0_1725881849389.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_embeddings_gbert_large_de_5.5.0_3.0_1725881849389.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
+documentAssembler = DocumentAssembler() \
+.setInputCol("text") \
+.setOutputCol("document")
+
+tokenizer = Tokenizer() \
+.setInputCols("document") \
+.setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("bert_embeddings_gbert_large","de") \
+.setInputCols(["document", "token"]) \
+.setOutputCol("embeddings")
+
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings])
+
+data = spark.createDataFrame([["Ich liebe Funken NLP"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+.setInputCol("text") 
+.setOutputCol("document")
+
+val tokenizer = new Tokenizer() 
+.setInputCols(Array("document"))
+.setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("bert_embeddings_gbert_large","de") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+
+val data = Seq("Ich liebe Funken NLP").toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("de.embed.gbert_large").predict("""Ich liebe Funken NLP""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_embeddings_gbert_large|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|de|
+|Size:|1.3 GB|
+
+## References
+
+References
+
+- https://huggingface.co/deepset/gbert-large
+- https://arxiv.org/pdf/2010.10906.pdf
+- https://arxiv.org/pdf/2010.10906.pdf
+- https://deepset.ai/german-bert
+- https://deepset.ai/germanquad
+- https://github.com/deepset-ai/FARM
+- https://github.com/deepset-ai/haystack/
+- https://twitter.com/deepset_ai
+- https://www.linkedin.com/company/deepset-ai/
+- https://haystack.deepset.ai/community/join
+- https://github.com/deepset-ai/haystack/discussions
+- https://deepset.ai
+- http://www.deepset.ai/jobs
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-bert_embeddings_gbert_large_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-09-bert_embeddings_gbert_large_pipeline_de.md
new file mode 100644
index 00000000000000..c0b114695a57c7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-bert_embeddings_gbert_large_pipeline_de.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: German bert_embeddings_gbert_large_pipeline pipeline BertEmbeddings from deepset
+author: John Snow Labs
+name: bert_embeddings_gbert_large_pipeline
+date: 2024-09-09
+tags: [de, open_source, pipeline, onnx]
+task: Embeddings
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_embeddings_gbert_large_pipeline` is a German model originally trained by deepset.
+
+{:.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/bert_embeddings_gbert_large_pipeline_de_5.5.0_3.0_1725881907742.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_embeddings_gbert_large_pipeline_de_5.5.0_3.0_1725881907742.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
+
+pipeline = PretrainedPipeline("bert_embeddings_gbert_large_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_embeddings_gbert_large_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_embeddings_gbert_large_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/deepset/gbert-large
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-bert_moral_emotion_kor_en.md b/docs/_posts/ahmedlone127/2024-09-09-bert_moral_emotion_kor_en.md
new file mode 100644
index 00000000000000..840b92eed62a75
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-bert_moral_emotion_kor_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English bert_moral_emotion_kor BertForSequenceClassification from Chaeyoon
+author: John Snow Labs
+name: bert_moral_emotion_kor
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_moral_emotion_kor` is a English model originally trained by Chaeyoon.
+
+{:.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/bert_moral_emotion_kor_en_5.5.0_3.0_1725856550998.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_moral_emotion_kor_en_5.5.0_3.0_1725856550998.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bert_moral_emotion_kor","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bert_moral_emotion_kor", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_moral_emotion_kor|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|408.5 MB|
+
+## References
+
+https://huggingface.co/Chaeyoon/BERT-Moral-Emotion-KOR
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-bert_samba_nan.md b/docs/_posts/ahmedlone127/2024-09-09-bert_samba_nan.md
new file mode 100644
index 00000000000000..577066525c502a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-bert_samba_nan.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: None bert_samba BertForSequenceClassification from tonynhan
+author: John Snow Labs
+name: bert_samba
+date: 2024-09-09
+tags: [nan, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: nan
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_samba` is a None model originally trained by tonynhan.
+
+{:.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/bert_samba_nan_5.5.0_3.0_1725853226412.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_samba_nan_5.5.0_3.0_1725853226412.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("bert_samba","nan") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("bert_samba", "nan")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_samba|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|nan|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/tonynhan/Bert_Samba
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-bert_samba_pipeline_nan.md b/docs/_posts/ahmedlone127/2024-09-09-bert_samba_pipeline_nan.md
new file mode 100644
index 00000000000000..63fd0f8f7778b4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-bert_samba_pipeline_nan.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: None bert_samba_pipeline pipeline BertForSequenceClassification from tonynhan
+author: John Snow Labs
+name: bert_samba_pipeline
+date: 2024-09-09
+tags: [nan, open_source, pipeline, onnx]
+task: Text Classification
+language: nan
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_samba_pipeline` is a None model originally trained by tonynhan.
+
+{:.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/bert_samba_pipeline_nan_5.5.0_3.0_1725853247040.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_samba_pipeline_nan_5.5.0_3.0_1725853247040.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
+
+pipeline = PretrainedPipeline("bert_samba_pipeline", lang = "nan")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("bert_samba_pipeline", lang = "nan")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_samba_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|nan|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/tonynhan/Bert_Samba
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-biobert_huner_gene_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-biobert_huner_gene_v1_pipeline_en.md
new file mode 100644
index 00000000000000..a9ffb48e0afa76
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-biobert_huner_gene_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English biobert_huner_gene_v1_pipeline pipeline BertForTokenClassification from aitslab
+author: John Snow Labs
+name: biobert_huner_gene_v1_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biobert_huner_gene_v1_pipeline` is a English model originally trained by aitslab.
+
+{:.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/biobert_huner_gene_v1_pipeline_en_5.5.0_3.0_1725886962568.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobert_huner_gene_v1_pipeline_en_5.5.0_3.0_1725886962568.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
+
+pipeline = PretrainedPipeline("biobert_huner_gene_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("biobert_huner_gene_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biobert_huner_gene_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|403.0 MB|
+
+## References
+
+https://huggingface.co/aitslab/biobert_huner_gene_v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-biomedbert_finetuned_pico_adishingote_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-biomedbert_finetuned_pico_adishingote_pipeline_en.md
new file mode 100644
index 00000000000000..424c6ef33a1dcb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-biomedbert_finetuned_pico_adishingote_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English biomedbert_finetuned_pico_adishingote_pipeline pipeline BertForTokenClassification from AdiShingote
+author: John Snow Labs
+name: biomedbert_finetuned_pico_adishingote_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biomedbert_finetuned_pico_adishingote_pipeline` is a English model originally trained by AdiShingote.
+
+{:.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/biomedbert_finetuned_pico_adishingote_pipeline_en_5.5.0_3.0_1725887446183.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biomedbert_finetuned_pico_adishingote_pipeline_en_5.5.0_3.0_1725887446183.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
+
+pipeline = PretrainedPipeline("biomedbert_finetuned_pico_adishingote_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("biomedbert_finetuned_pico_adishingote_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|biomedbert_finetuned_pico_adishingote_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.2 MB|
+
+## References
+
+https://huggingface.co/AdiShingote/Biomedbert-finetuned-PICO
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForTokenClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-boolq_microsoft_deberta_v3_large_seed_1_en.md b/docs/_posts/ahmedlone127/2024-09-09-boolq_microsoft_deberta_v3_large_seed_1_en.md
new file mode 100644
index 00000000000000..79b10ce0eff093
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-boolq_microsoft_deberta_v3_large_seed_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English boolq_microsoft_deberta_v3_large_seed_1 DeBertaForSequenceClassification from utahnlp
+author: John Snow Labs
+name: boolq_microsoft_deberta_v3_large_seed_1
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`boolq_microsoft_deberta_v3_large_seed_1` is a English model originally trained by utahnlp.
+
+{:.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/boolq_microsoft_deberta_v3_large_seed_1_en_5.5.0_3.0_1725848580775.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/boolq_microsoft_deberta_v3_large_seed_1_en_5.5.0_3.0_1725848580775.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("boolq_microsoft_deberta_v3_large_seed_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("boolq_microsoft_deberta_v3_large_seed_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|boolq_microsoft_deberta_v3_large_seed_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/utahnlp/boolq_microsoft_deberta-v3-large_seed-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-boolq_microsoft_deberta_v3_large_seed_2_en.md b/docs/_posts/ahmedlone127/2024-09-09-boolq_microsoft_deberta_v3_large_seed_2_en.md
new file mode 100644
index 00000000000000..8ba091a115831d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-boolq_microsoft_deberta_v3_large_seed_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English boolq_microsoft_deberta_v3_large_seed_2 DeBertaForSequenceClassification from utahnlp
+author: John Snow Labs
+name: boolq_microsoft_deberta_v3_large_seed_2
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`boolq_microsoft_deberta_v3_large_seed_2` is a English model originally trained by utahnlp.
+
+{:.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/boolq_microsoft_deberta_v3_large_seed_2_en_5.5.0_3.0_1725849304671.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/boolq_microsoft_deberta_v3_large_seed_2_en_5.5.0_3.0_1725849304671.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("boolq_microsoft_deberta_v3_large_seed_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("boolq_microsoft_deberta_v3_large_seed_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|boolq_microsoft_deberta_v3_large_seed_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/utahnlp/boolq_microsoft_deberta-v3-large_seed-2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-boolq_microsoft_deberta_v3_large_seed_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-boolq_microsoft_deberta_v3_large_seed_2_pipeline_en.md
new file mode 100644
index 00000000000000..d7fde3ed5a034a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-boolq_microsoft_deberta_v3_large_seed_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English boolq_microsoft_deberta_v3_large_seed_2_pipeline pipeline DeBertaForSequenceClassification from utahnlp
+author: John Snow Labs
+name: boolq_microsoft_deberta_v3_large_seed_2_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`boolq_microsoft_deberta_v3_large_seed_2_pipeline` is a English model originally trained by utahnlp.
+
+{:.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/boolq_microsoft_deberta_v3_large_seed_2_pipeline_en_5.5.0_3.0_1725849416849.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/boolq_microsoft_deberta_v3_large_seed_2_pipeline_en_5.5.0_3.0_1725849416849.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
+
+pipeline = PretrainedPipeline("boolq_microsoft_deberta_v3_large_seed_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("boolq_microsoft_deberta_v3_large_seed_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|boolq_microsoft_deberta_v3_large_seed_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/utahnlp/boolq_microsoft_deberta-v3-large_seed-2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_0uma_en.md b/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_0uma_en.md
new file mode 100644
index 00000000000000..2245d5013137d5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_0uma_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_0uma DistilBertForQuestionAnswering from 0uma
+author: John Snow Labs
+name: burmese_awesome_qa_model_0uma
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_0uma` is a English model originally trained by 0uma.
+
+{:.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/burmese_awesome_qa_model_0uma_en_5.5.0_3.0_1725877220779.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_0uma_en_5.5.0_3.0_1725877220779.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_0uma","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_0uma", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_0uma|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/0uma/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_0uma_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_0uma_pipeline_en.md
new file mode 100644
index 00000000000000..227d7dfbbea975
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_0uma_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_0uma_pipeline pipeline DistilBertForQuestionAnswering from 0uma
+author: John Snow Labs
+name: burmese_awesome_qa_model_0uma_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_0uma_pipeline` is a English model originally trained by 0uma.
+
+{:.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/burmese_awesome_qa_model_0uma_pipeline_en_5.5.0_3.0_1725877233380.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_0uma_pipeline_en_5.5.0_3.0_1725877233380.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_0uma_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_0uma_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_0uma_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/0uma/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_bloomlonely_en.md b/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_bloomlonely_en.md
new file mode 100644
index 00000000000000..ecc97b105d1dad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_bloomlonely_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_bloomlonely DistilBertForQuestionAnswering from BloomLonely
+author: John Snow Labs
+name: burmese_awesome_qa_model_bloomlonely
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_bloomlonely` is a English model originally trained by BloomLonely.
+
+{:.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/burmese_awesome_qa_model_bloomlonely_en_5.5.0_3.0_1725877337496.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_bloomlonely_en_5.5.0_3.0_1725877337496.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_bloomlonely","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_bloomlonely", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_bloomlonely|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/BloomLonely/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_prinslayy_16_en.md b/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_prinslayy_16_en.md
new file mode 100644
index 00000000000000..5d4b0ae4e58bf6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_prinslayy_16_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_prinslayy_16 DistilBertForQuestionAnswering from prinslayy-16
+author: John Snow Labs
+name: burmese_awesome_qa_model_prinslayy_16
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_prinslayy_16` is a English model originally trained by prinslayy-16.
+
+{:.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/burmese_awesome_qa_model_prinslayy_16_en_5.5.0_3.0_1725877045139.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_prinslayy_16_en_5.5.0_3.0_1725877045139.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_prinslayy_16","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_prinslayy_16", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_prinslayy_16|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/prinslayy-16/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_raffenmb_en.md b/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_raffenmb_en.md
new file mode 100644
index 00000000000000..df41d6abd6a466
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_raffenmb_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_raffenmb DistilBertForQuestionAnswering from raffenmb
+author: John Snow Labs
+name: burmese_awesome_qa_model_raffenmb
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_raffenmb` is a English model originally trained by raffenmb.
+
+{:.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/burmese_awesome_qa_model_raffenmb_en_5.5.0_3.0_1725868737709.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_raffenmb_en_5.5.0_3.0_1725868737709.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_raffenmb","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_raffenmb", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_raffenmb|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/raffenmb/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_saudi82s_en.md b/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_saudi82s_en.md
new file mode 100644
index 00000000000000..592e1d78f75626
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_saudi82s_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_saudi82s DistilBertForQuestionAnswering from saudi82s
+author: John Snow Labs
+name: burmese_awesome_qa_model_saudi82s
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_saudi82s` is a English model originally trained by saudi82s.
+
+{:.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/burmese_awesome_qa_model_saudi82s_en_5.5.0_3.0_1725869312354.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_saudi82s_en_5.5.0_3.0_1725869312354.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_saudi82s","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_saudi82s", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_saudi82s|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|104.3 MB|
+
+## References
+
+https://huggingface.co/saudi82s/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_selbl_en.md b/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_selbl_en.md
new file mode 100644
index 00000000000000..dcf01dd8417917
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_selbl_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_selbl DistilBertForQuestionAnswering from selbl
+author: John Snow Labs
+name: burmese_awesome_qa_model_selbl
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_selbl` is a English model originally trained by selbl.
+
+{:.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/burmese_awesome_qa_model_selbl_en_5.5.0_3.0_1725876852675.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_selbl_en_5.5.0_3.0_1725876852675.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_selbl","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_selbl", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_selbl|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/selbl/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_selbl_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_selbl_pipeline_en.md
new file mode 100644
index 00000000000000..dc6edd92c25fa3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_selbl_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_selbl_pipeline pipeline DistilBertForQuestionAnswering from selbl
+author: John Snow Labs
+name: burmese_awesome_qa_model_selbl_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_selbl_pipeline` is a English model originally trained by selbl.
+
+{:.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/burmese_awesome_qa_model_selbl_pipeline_en_5.5.0_3.0_1725876864065.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_selbl_pipeline_en_5.5.0_3.0_1725876864065.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_selbl_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_selbl_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_selbl_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/selbl/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_tealeafs_en.md b/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_tealeafs_en.md
new file mode 100644
index 00000000000000..8404cb5a72c56d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_tealeafs_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_tealeafs DistilBertForQuestionAnswering from TeaLeafs
+author: John Snow Labs
+name: burmese_awesome_qa_model_tealeafs
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_tealeafs` is a English model originally trained by TeaLeafs.
+
+{:.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/burmese_awesome_qa_model_tealeafs_en_5.5.0_3.0_1725869349367.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_tealeafs_en_5.5.0_3.0_1725869349367.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_tealeafs","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_tealeafs", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_tealeafs|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/TeaLeafs/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_tealeafs_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_tealeafs_pipeline_en.md
new file mode 100644
index 00000000000000..92ea961309813f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_tealeafs_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_tealeafs_pipeline pipeline DistilBertForQuestionAnswering from TeaLeafs
+author: John Snow Labs
+name: burmese_awesome_qa_model_tealeafs_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_tealeafs_pipeline` is a English model originally trained by TeaLeafs.
+
+{:.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/burmese_awesome_qa_model_tealeafs_pipeline_en_5.5.0_3.0_1725869361445.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_tealeafs_pipeline_en_5.5.0_3.0_1725869361445.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_tealeafs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_tealeafs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_tealeafs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/TeaLeafs/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_ylei_en.md b/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_ylei_en.md
new file mode 100644
index 00000000000000..6d741f77a33ac1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_ylei_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_ylei DistilBertForQuestionAnswering from ylei
+author: John Snow Labs
+name: burmese_awesome_qa_model_ylei
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_ylei` is a English model originally trained by ylei.
+
+{:.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/burmese_awesome_qa_model_ylei_en_5.5.0_3.0_1725868908825.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_ylei_en_5.5.0_3.0_1725868908825.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_ylei","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_ylei", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_ylei|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/ylei/my_awesome_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_ylei_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_ylei_pipeline_en.md
new file mode 100644
index 00000000000000..167d420593fe0a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_qa_model_ylei_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English burmese_awesome_qa_model_ylei_pipeline pipeline DistilBertForQuestionAnswering from ylei
+author: John Snow Labs
+name: burmese_awesome_qa_model_ylei_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_ylei_pipeline` is a English model originally trained by ylei.
+
+{:.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/burmese_awesome_qa_model_ylei_pipeline_en_5.5.0_3.0_1725868923193.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_ylei_pipeline_en_5.5.0_3.0_1725868923193.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
+
+pipeline = PretrainedPipeline("burmese_awesome_qa_model_ylei_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_ylei_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_qa_model_ylei_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/ylei/my_awesome_qa_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_wnut_model_catbult_en.md b/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_wnut_model_catbult_en.md
new file mode 100644
index 00000000000000..d202c79a7f5f33
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-burmese_awesome_wnut_model_catbult_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English burmese_awesome_wnut_model_catbult DistilBertForTokenClassification from catbult
+author: John Snow Labs
+name: burmese_awesome_wnut_model_catbult
+date: 2024-09-09
+tags: [en, open_source, onnx, token_classification, distilbert, ner]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_wnut_model_catbult` is a English model originally trained by catbult.
+
+{:.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/burmese_awesome_wnut_model_catbult_en_5.5.0_3.0_1725890129890.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_wnut_model_catbult_en_5.5.0_3.0_1725890129890.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+tokenClassifier  = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_catbult","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols("document")
+    .setOutputCol("token")
+
+val tokenClassifier = DistilBertForTokenClassification.pretrained("burmese_awesome_wnut_model_catbult", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|burmese_awesome_wnut_model_catbult|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/catbult/my_awesome_wnut_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-case_analysis_legal_bert_base_uncased_en.md b/docs/_posts/ahmedlone127/2024-09-09-case_analysis_legal_bert_base_uncased_en.md
new file mode 100644
index 00000000000000..ea067f5a2e4c9e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-case_analysis_legal_bert_base_uncased_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English case_analysis_legal_bert_base_uncased BertForSequenceClassification from cite-text-analysis
+author: John Snow Labs
+name: case_analysis_legal_bert_base_uncased
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`case_analysis_legal_bert_base_uncased` is a English model originally trained by cite-text-analysis.
+
+{:.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/case_analysis_legal_bert_base_uncased_en_5.5.0_3.0_1725852652851.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/case_analysis_legal_bert_base_uncased_en_5.5.0_3.0_1725852652851.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("case_analysis_legal_bert_base_uncased","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("case_analysis_legal_bert_base_uncased", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|case_analysis_legal_bert_base_uncased|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.5 MB|
+
+## References
+
+https://huggingface.co/cite-text-analysis/case-analysis-legal-bert-base-uncased
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis_nlp_feup_en.md b/docs/_posts/ahmedlone127/2024-09-09-danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis_nlp_feup_en.md
new file mode 100644
index 00000000000000..4254b87fec3e0f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis_nlp_feup_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis_nlp_feup RoBertaEmbeddings from NLP-FEUP
+author: John Snow Labs
+name: danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis_nlp_feup
+date: 2024-09-09
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis_nlp_feup` is a English model originally trained by NLP-FEUP.
+
+{:.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/danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis_nlp_feup_en_5.5.0_3.0_1725882879173.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis_nlp_feup_en_5.5.0_3.0_1725882879173.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis_nlp_feup","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis_nlp_feup","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|danish_mrm8488_distilroberta_finetuned_financial_news_sentiment_analysis_nlp_feup|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|306.8 MB|
+
+## References
+
+https://huggingface.co/NLP-FEUP/DA-mrm8488-distilroberta-finetuned-financial-news-sentiment-analysis
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-deberta_attr_score_140_en.md b/docs/_posts/ahmedlone127/2024-09-09-deberta_attr_score_140_en.md
new file mode 100644
index 00000000000000..f9f4f204f19adb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-deberta_attr_score_140_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_attr_score_140 DeBertaForSequenceClassification from Josef0801
+author: John Snow Labs
+name: deberta_attr_score_140
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_attr_score_140` is a English model originally trained by Josef0801.
+
+{:.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/deberta_attr_score_140_en_5.5.0_3.0_1725848533499.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_attr_score_140_en_5.5.0_3.0_1725848533499.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_attr_score_140","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_attr_score_140", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_attr_score_140|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|665.7 MB|
+
+## References
+
+https://huggingface.co/Josef0801/deberta_attr_score_140
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-deberta_attr_score_140_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-deberta_attr_score_140_pipeline_en.md
new file mode 100644
index 00000000000000..34c3b7936d70ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-deberta_attr_score_140_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_attr_score_140_pipeline pipeline DeBertaForSequenceClassification from Josef0801
+author: John Snow Labs
+name: deberta_attr_score_140_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_attr_score_140_pipeline` is a English model originally trained by Josef0801.
+
+{:.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/deberta_attr_score_140_pipeline_en_5.5.0_3.0_1725848568914.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_attr_score_140_pipeline_en_5.5.0_3.0_1725848568914.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
+
+pipeline = PretrainedPipeline("deberta_attr_score_140_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_attr_score_140_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_attr_score_140_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|665.7 MB|
+
+## References
+
+https://huggingface.co/Josef0801/deberta_attr_score_140
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-deberta_docnli_sentencelevel_ner_all_en.md b/docs/_posts/ahmedlone127/2024-09-09-deberta_docnli_sentencelevel_ner_all_en.md
new file mode 100644
index 00000000000000..9cbdd6203a8e49
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-deberta_docnli_sentencelevel_ner_all_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_docnli_sentencelevel_ner_all DeBertaForSequenceClassification from jeffyelson
+author: John Snow Labs
+name: deberta_docnli_sentencelevel_ner_all
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_docnli_sentencelevel_ner_all` is a English model originally trained by jeffyelson.
+
+{:.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/deberta_docnli_sentencelevel_ner_all_en_5.5.0_3.0_1725848372967.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_docnli_sentencelevel_ner_all_en_5.5.0_3.0_1725848372967.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_docnli_sentencelevel_ner_all","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_docnli_sentencelevel_ner_all", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_docnli_sentencelevel_ner_all|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|594.3 MB|
+
+## References
+
+https://huggingface.co/jeffyelson/deberta_docnli_sentencelevel_ner_all
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-deberta_docnli_sentencelevel_ner_all_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-deberta_docnli_sentencelevel_ner_all_pipeline_en.md
new file mode 100644
index 00000000000000..030cd96254a293
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-deberta_docnli_sentencelevel_ner_all_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_docnli_sentencelevel_ner_all_pipeline pipeline DeBertaForSequenceClassification from jeffyelson
+author: John Snow Labs
+name: deberta_docnli_sentencelevel_ner_all_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_docnli_sentencelevel_ner_all_pipeline` is a English model originally trained by jeffyelson.
+
+{:.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/deberta_docnli_sentencelevel_ner_all_pipeline_en_5.5.0_3.0_1725848412040.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_docnli_sentencelevel_ner_all_pipeline_en_5.5.0_3.0_1725848412040.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
+
+pipeline = PretrainedPipeline("deberta_docnli_sentencelevel_ner_all_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_docnli_sentencelevel_ner_all_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_docnli_sentencelevel_ner_all_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|594.3 MB|
+
+## References
+
+https://huggingface.co/jeffyelson/deberta_docnli_sentencelevel_ner_all
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-deberta_docnli_sentencelevel_nofeatures_en.md b/docs/_posts/ahmedlone127/2024-09-09-deberta_docnli_sentencelevel_nofeatures_en.md
new file mode 100644
index 00000000000000..1c1a1ee1cc4e49
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-deberta_docnli_sentencelevel_nofeatures_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_docnli_sentencelevel_nofeatures DeBertaForSequenceClassification from jeffyelson
+author: John Snow Labs
+name: deberta_docnli_sentencelevel_nofeatures
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_docnli_sentencelevel_nofeatures` is a English model originally trained by jeffyelson.
+
+{:.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/deberta_docnli_sentencelevel_nofeatures_en_5.5.0_3.0_1725879911149.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_docnli_sentencelevel_nofeatures_en_5.5.0_3.0_1725879911149.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_docnli_sentencelevel_nofeatures","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_docnli_sentencelevel_nofeatures", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_docnli_sentencelevel_nofeatures|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|591.6 MB|
+
+## References
+
+https://huggingface.co/jeffyelson/deberta_docnli_sentencelevel_nofeatures
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_fever_en.md b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_fever_en.md
new file mode 100644
index 00000000000000..b08a411bc1c248
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_fever_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_base_fever DeBertaForSequenceClassification from pepa
+author: John Snow Labs
+name: deberta_v3_base_fever
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_fever` is a English model originally trained by pepa.
+
+{:.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/deberta_v3_base_fever_en_5.5.0_3.0_1725848801146.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_fever_en_5.5.0_3.0_1725848801146.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_base_fever","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_fever", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_fever|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|644.1 MB|
+
+## References
+
+https://huggingface.co/pepa/deberta-v3-base-fever
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_fever_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_fever_pipeline_en.md
new file mode 100644
index 00000000000000..905db1329f79f1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_fever_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_base_fever_pipeline pipeline DeBertaForSequenceClassification from pepa
+author: John Snow Labs
+name: deberta_v3_base_fever_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_fever_pipeline` is a English model originally trained by pepa.
+
+{:.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/deberta_v3_base_fever_pipeline_en_5.5.0_3.0_1725848844596.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_fever_pipeline_en_5.5.0_3.0_1725848844596.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
+
+pipeline = PretrainedPipeline("deberta_v3_base_fever_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_base_fever_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_fever_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|644.1 MB|
+
+## References
+
+https://huggingface.co/pepa/deberta-v3-base-fever
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_finetuned_uf_ner_6x_0type_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_finetuned_uf_ner_6x_0type_v1_pipeline_en.md
new file mode 100644
index 00000000000000..74c52f93a8d220
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_finetuned_uf_ner_6x_0type_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_base_finetuned_uf_ner_6x_0type_v1_pipeline pipeline DeBertaForSequenceClassification from mariolinml
+author: John Snow Labs
+name: deberta_v3_base_finetuned_uf_ner_6x_0type_v1_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_finetuned_uf_ner_6x_0type_v1_pipeline` is a English model originally trained by mariolinml.
+
+{:.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/deberta_v3_base_finetuned_uf_ner_6x_0type_v1_pipeline_en_5.5.0_3.0_1725859098387.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_finetuned_uf_ner_6x_0type_v1_pipeline_en_5.5.0_3.0_1725859098387.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
+
+pipeline = PretrainedPipeline("deberta_v3_base_finetuned_uf_ner_6x_0type_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_base_finetuned_uf_ner_6x_0type_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_finetuned_uf_ner_6x_0type_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|577.8 MB|
+
+## References
+
+https://huggingface.co/mariolinml/deberta-v3-base-finetuned-uf-ner-6X-0type_v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_glue_rte_en.md b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_glue_rte_en.md
new file mode 100644
index 00000000000000..8e160eed3232d3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_glue_rte_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_base_glue_rte DeBertaForSequenceClassification from ficsort
+author: John Snow Labs
+name: deberta_v3_base_glue_rte
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_glue_rte` is a English model originally trained by ficsort.
+
+{:.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/deberta_v3_base_glue_rte_en_5.5.0_3.0_1725849988844.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_glue_rte_en_5.5.0_3.0_1725849988844.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_base_glue_rte","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_glue_rte", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_glue_rte|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|585.8 MB|
+
+## References
+
+https://huggingface.co/ficsort/deberta-v3-base-glue-rte
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_hate_speech_offensive_en.md b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_hate_speech_offensive_en.md
new file mode 100644
index 00000000000000..d0c4dd1b0de1ae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_hate_speech_offensive_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_base_hate_speech_offensive DeBertaForSequenceClassification from kietnt0603
+author: John Snow Labs
+name: deberta_v3_base_hate_speech_offensive
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_hate_speech_offensive` is a English model originally trained by kietnt0603.
+
+{:.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/deberta_v3_base_hate_speech_offensive_en_5.5.0_3.0_1725880087095.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_hate_speech_offensive_en_5.5.0_3.0_1725880087095.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_base_hate_speech_offensive","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_hate_speech_offensive", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_hate_speech_offensive|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|593.3 MB|
+
+## References
+
+https://huggingface.co/kietnt0603/deberta-v3-base-hate-speech-offensive
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_isarcasm_en.md b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_isarcasm_en.md
new file mode 100644
index 00000000000000..3be2a7a7fdcbed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_isarcasm_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_base_isarcasm DeBertaForSequenceClassification from w11wo
+author: John Snow Labs
+name: deberta_v3_base_isarcasm
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_isarcasm` is a English model originally trained by w11wo.
+
+{:.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/deberta_v3_base_isarcasm_en_5.5.0_3.0_1725848403334.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_isarcasm_en_5.5.0_3.0_1725848403334.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_base_isarcasm","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_isarcasm", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_isarcasm|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|579.4 MB|
+
+## References
+
+https://huggingface.co/w11wo/deberta-v3-base-isarcasm
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_isarcasm_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_isarcasm_pipeline_en.md
new file mode 100644
index 00000000000000..58df3b2cbdc2e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_isarcasm_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_base_isarcasm_pipeline pipeline DeBertaForSequenceClassification from w11wo
+author: John Snow Labs
+name: deberta_v3_base_isarcasm_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_isarcasm_pipeline` is a English model originally trained by w11wo.
+
+{:.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/deberta_v3_base_isarcasm_pipeline_en_5.5.0_3.0_1725848470441.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_isarcasm_pipeline_en_5.5.0_3.0_1725848470441.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
+
+pipeline = PretrainedPipeline("deberta_v3_base_isarcasm_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_base_isarcasm_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_isarcasm_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|579.4 MB|
+
+## References
+
+https://huggingface.co/w11wo/deberta-v3-base-isarcasm
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_otat_recommened_hp_en.md b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_otat_recommened_hp_en.md
new file mode 100644
index 00000000000000..3b9902b9527ef3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_otat_recommened_hp_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_base_otat_recommened_hp DeBertaForSequenceClassification from DandinPower
+author: John Snow Labs
+name: deberta_v3_base_otat_recommened_hp
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_otat_recommened_hp` is a English model originally trained by DandinPower.
+
+{:.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/deberta_v3_base_otat_recommened_hp_en_5.5.0_3.0_1725850185730.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_otat_recommened_hp_en_5.5.0_3.0_1725850185730.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_base_otat_recommened_hp","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_otat_recommened_hp", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_otat_recommened_hp|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|604.9 MB|
+
+## References
+
+https://huggingface.co/DandinPower/deberta-v3-base-otat-recommened-hp
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_otat_recommened_hp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_otat_recommened_hp_pipeline_en.md
new file mode 100644
index 00000000000000..2e05bf19cab006
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_otat_recommened_hp_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_base_otat_recommened_hp_pipeline pipeline DeBertaForSequenceClassification from DandinPower
+author: John Snow Labs
+name: deberta_v3_base_otat_recommened_hp_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_otat_recommened_hp_pipeline` is a English model originally trained by DandinPower.
+
+{:.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/deberta_v3_base_otat_recommened_hp_pipeline_en_5.5.0_3.0_1725850241070.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_otat_recommened_hp_pipeline_en_5.5.0_3.0_1725850241070.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
+
+pipeline = PretrainedPipeline("deberta_v3_base_otat_recommened_hp_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_base_otat_recommened_hp_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_otat_recommened_hp_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|604.9 MB|
+
+## References
+
+https://huggingface.co/DandinPower/deberta-v3-base-otat-recommened-hp
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_rte_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_rte_pipeline_en.md
new file mode 100644
index 00000000000000..9eb155c15f7ecf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_rte_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_base_rte_pipeline pipeline DeBertaForSequenceClassification from cliang1453
+author: John Snow Labs
+name: deberta_v3_base_rte_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_rte_pipeline` is a English model originally trained by cliang1453.
+
+{:.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/deberta_v3_base_rte_pipeline_en_5.5.0_3.0_1725848652282.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_rte_pipeline_en_5.5.0_3.0_1725848652282.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
+
+pipeline = PretrainedPipeline("deberta_v3_base_rte_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_base_rte_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_rte_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|579.4 MB|
+
+## References
+
+https://huggingface.co/cliang1453/deberta-v3-base-rte
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_v_1_en.md b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_v_1_en.md
new file mode 100644
index 00000000000000..d1044691f3a7f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_base_v_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_base_v_1 DeBertaForSequenceClassification from taskydata
+author: John Snow Labs
+name: deberta_v3_base_v_1
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_base_v_1` is a English model originally trained by taskydata.
+
+{:.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/deberta_v3_base_v_1_en_5.5.0_3.0_1725850170361.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_base_v_1_en_5.5.0_3.0_1725850170361.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_base_v_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_base_v_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_base_v_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|691.6 MB|
+
+## References
+
+https://huggingface.co/taskydata/deberta-v3-base_v_1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_large__sst2__train_8_9_en.md b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_large__sst2__train_8_9_en.md
new file mode 100644
index 00000000000000..5c596eef9d02ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_large__sst2__train_8_9_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_large__sst2__train_8_9 DeBertaForSequenceClassification from SetFit
+author: John Snow Labs
+name: deberta_v3_large__sst2__train_8_9
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large__sst2__train_8_9` is a English model originally trained by SetFit.
+
+{:.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/deberta_v3_large__sst2__train_8_9_en_5.5.0_3.0_1725848791039.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_8_9_en_5.5.0_3.0_1725848791039.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_large__sst2__train_8_9","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large__sst2__train_8_9", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large__sst2__train_8_9|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/SetFit/deberta-v3-large__sst2__train-8-9
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_large__sst2__train_8_9_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_large__sst2__train_8_9_pipeline_en.md
new file mode 100644
index 00000000000000..c3f1f396919902
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_large__sst2__train_8_9_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_large__sst2__train_8_9_pipeline pipeline DeBertaForSequenceClassification from SetFit
+author: John Snow Labs
+name: deberta_v3_large__sst2__train_8_9_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large__sst2__train_8_9_pipeline` is a English model originally trained by SetFit.
+
+{:.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/deberta_v3_large__sst2__train_8_9_pipeline_en_5.5.0_3.0_1725848905065.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large__sst2__train_8_9_pipeline_en_5.5.0_3.0_1725848905065.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
+
+pipeline = PretrainedPipeline("deberta_v3_large__sst2__train_8_9_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large__sst2__train_8_9_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large__sst2__train_8_9_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/SetFit/deberta-v3-large__sst2__train-8-9
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_large_survey_fluency_rater_all_gpt4_en.md b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_large_survey_fluency_rater_all_gpt4_en.md
new file mode 100644
index 00000000000000..a1fde2b9aeea7a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_large_survey_fluency_rater_all_gpt4_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_large_survey_fluency_rater_all_gpt4 DeBertaForSequenceClassification from domenicrosati
+author: John Snow Labs
+name: deberta_v3_large_survey_fluency_rater_all_gpt4
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_survey_fluency_rater_all_gpt4` is a English model originally trained by domenicrosati.
+
+{:.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/deberta_v3_large_survey_fluency_rater_all_gpt4_en_5.5.0_3.0_1725879125852.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_fluency_rater_all_gpt4_en_5.5.0_3.0_1725879125852.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_large_survey_fluency_rater_all_gpt4","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_large_survey_fluency_rater_all_gpt4", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_survey_fluency_rater_all_gpt4|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/domenicrosati/deberta-v3-large-survey-fluency-rater-all-gpt4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_large_survey_fluency_rater_all_gpt4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_large_survey_fluency_rater_all_gpt4_pipeline_en.md
new file mode 100644
index 00000000000000..d7fc77a2aea03f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_large_survey_fluency_rater_all_gpt4_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_large_survey_fluency_rater_all_gpt4_pipeline pipeline DeBertaForSequenceClassification from domenicrosati
+author: John Snow Labs
+name: deberta_v3_large_survey_fluency_rater_all_gpt4_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_survey_fluency_rater_all_gpt4_pipeline` is a English model originally trained by domenicrosati.
+
+{:.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/deberta_v3_large_survey_fluency_rater_all_gpt4_pipeline_en_5.5.0_3.0_1725879218368.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_survey_fluency_rater_all_gpt4_pipeline_en_5.5.0_3.0_1725879218368.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
+
+pipeline = PretrainedPipeline("deberta_v3_large_survey_fluency_rater_all_gpt4_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_large_survey_fluency_rater_all_gpt4_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_large_survey_fluency_rater_all_gpt4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/domenicrosati/deberta-v3-large-survey-fluency-rater-all-gpt4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_small_finetuned_rte_en.md b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_small_finetuned_rte_en.md
new file mode 100644
index 00000000000000..90135211b5ac76
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_small_finetuned_rte_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_small_finetuned_rte DeBertaForSequenceClassification from rdp99
+author: John Snow Labs
+name: deberta_v3_small_finetuned_rte
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_finetuned_rte` is a English model originally trained by rdp99.
+
+{:.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/deberta_v3_small_finetuned_rte_en_5.5.0_3.0_1725880133711.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_finetuned_rte_en_5.5.0_3.0_1725880133711.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_small_finetuned_rte","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_small_finetuned_rte", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_small_finetuned_rte|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|430.9 MB|
+
+## References
+
+https://huggingface.co/rdp99/deberta-v3-small-finetuned-rte
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_small_finetuned_rte_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_small_finetuned_rte_pipeline_en.md
new file mode 100644
index 00000000000000..4d0c1aedf0c2c3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_small_finetuned_rte_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_small_finetuned_rte_pipeline pipeline DeBertaForSequenceClassification from rdp99
+author: John Snow Labs
+name: deberta_v3_small_finetuned_rte_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_finetuned_rte_pipeline` is a English model originally trained by rdp99.
+
+{:.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/deberta_v3_small_finetuned_rte_pipeline_en_5.5.0_3.0_1725880189464.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_finetuned_rte_pipeline_en_5.5.0_3.0_1725880189464.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
+
+pipeline = PretrainedPipeline("deberta_v3_small_finetuned_rte_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_small_finetuned_rte_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_small_finetuned_rte_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|430.9 MB|
+
+## References
+
+https://huggingface.co/rdp99/deberta-v3-small-finetuned-rte
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_small_test_ver1_en.md b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_small_test_ver1_en.md
new file mode 100644
index 00000000000000..86bb23b0b97cc1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_small_test_ver1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_small_test_ver1 DeBertaForSequenceClassification from YujiK
+author: John Snow Labs
+name: deberta_v3_small_test_ver1
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_test_ver1` is a English model originally trained by YujiK.
+
+{:.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/deberta_v3_small_test_ver1_en_5.5.0_3.0_1725849316032.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_test_ver1_en_5.5.0_3.0_1725849316032.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_small_test_ver1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_small_test_ver1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_small_test_ver1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|432.1 MB|
+
+## References
+
+https://huggingface.co/YujiK/deberta-v3-small-test_ver1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_small_test_ver1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_small_test_ver1_pipeline_en.md
new file mode 100644
index 00000000000000..193dac1ea02730
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_small_test_ver1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_small_test_ver1_pipeline pipeline DeBertaForSequenceClassification from YujiK
+author: John Snow Labs
+name: deberta_v3_small_test_ver1_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_small_test_ver1_pipeline` is a English model originally trained by YujiK.
+
+{:.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/deberta_v3_small_test_ver1_pipeline_en_5.5.0_3.0_1725849347724.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_small_test_ver1_pipeline_en_5.5.0_3.0_1725849347724.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
+
+pipeline = PretrainedPipeline("deberta_v3_small_test_ver1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_small_test_ver1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_small_test_ver1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|432.1 MB|
+
+## References
+
+https://huggingface.co/YujiK/deberta-v3-small-test_ver1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_xsmall_emotion_en.md b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_xsmall_emotion_en.md
new file mode 100644
index 00000000000000..7663fb6ea466c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_xsmall_emotion_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English deberta_v3_xsmall_emotion DeBertaForSequenceClassification from philschmid
+author: John Snow Labs
+name: deberta_v3_xsmall_emotion
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_emotion` is a English model originally trained by philschmid.
+
+{:.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/deberta_v3_xsmall_emotion_en_5.5.0_3.0_1725879708725.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_emotion_en_5.5.0_3.0_1725879708725.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deberta_v3_xsmall_emotion","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deberta_v3_xsmall_emotion", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_xsmall_emotion|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|208.4 MB|
+
+## References
+
+https://huggingface.co/philschmid/deberta-v3-xsmall-emotion
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_xsmall_emotion_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_xsmall_emotion_pipeline_en.md
new file mode 100644
index 00000000000000..c8ff442da15466
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-deberta_v3_xsmall_emotion_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English deberta_v3_xsmall_emotion_pipeline pipeline DeBertaForSequenceClassification from philschmid
+author: John Snow Labs
+name: deberta_v3_xsmall_emotion_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_xsmall_emotion_pipeline` is a English model originally trained by philschmid.
+
+{:.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/deberta_v3_xsmall_emotion_pipeline_en_5.5.0_3.0_1725879742293.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_xsmall_emotion_pipeline_en_5.5.0_3.0_1725879742293.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
+
+pipeline = PretrainedPipeline("deberta_v3_xsmall_emotion_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("deberta_v3_xsmall_emotion_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deberta_v3_xsmall_emotion_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|208.4 MB|
+
+## References
+
+https://huggingface.co/philschmid/deberta-v3-xsmall-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-deneme_model_eng_en.md b/docs/_posts/ahmedlone127/2024-09-09-deneme_model_eng_en.md
new file mode 100644
index 00000000000000..d242c8ef55afb9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-deneme_model_eng_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English deneme_model_eng DistilBertForQuestionAnswering from yegokpinar
+author: John Snow Labs
+name: deneme_model_eng
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deneme_model_eng` is a English model originally trained by yegokpinar.
+
+{:.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/deneme_model_eng_en_5.5.0_3.0_1725876818377.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deneme_model_eng_en_5.5.0_3.0_1725876818377.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("deneme_model_eng","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("deneme_model_eng", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deneme_model_eng|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/yegokpinar/deneme_model_eng
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-deprem_mdeberta_binary_tr.md b/docs/_posts/ahmedlone127/2024-09-09-deprem_mdeberta_binary_tr.md
new file mode 100644
index 00000000000000..c1d3ba1bb40221
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-deprem_mdeberta_binary_tr.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Turkish deprem_mdeberta_binary DeBertaForSequenceClassification from ctoraman
+author: John Snow Labs
+name: deprem_mdeberta_binary
+date: 2024-09-09
+tags: [tr, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: tr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deprem_mdeberta_binary` is a Turkish model originally trained by ctoraman.
+
+{:.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/deprem_mdeberta_binary_tr_5.5.0_3.0_1725880463884.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deprem_mdeberta_binary_tr_5.5.0_3.0_1725880463884.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("deprem_mdeberta_binary","tr") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("deprem_mdeberta_binary", "tr")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|deprem_mdeberta_binary|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|tr|
+|Size:|791.2 MB|
+
+## References
+
+https://huggingface.co/ctoraman/deprem-mdeberta-binary
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-discord_distilbert_en.md b/docs/_posts/ahmedlone127/2024-09-09-discord_distilbert_en.md
new file mode 100644
index 00000000000000..41e5e69fae5673
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-discord_distilbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English discord_distilbert DistilBertEmbeddings from windshield-viper
+author: John Snow Labs
+name: discord_distilbert
+date: 2024-09-09
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`discord_distilbert` is a English model originally trained by windshield-viper.
+
+{:.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/discord_distilbert_en_5.5.0_3.0_1725878299471.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/discord_distilbert_en_5.5.0_3.0_1725878299471.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("discord_distilbert","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("discord_distilbert","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|discord_distilbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/windshield-viper/discord-distilbert
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-disitlbert_finetunedmodel_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-disitlbert_finetunedmodel_pipeline_en.md
new file mode 100644
index 00000000000000..96a5dc7bd97fff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-disitlbert_finetunedmodel_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English disitlbert_finetunedmodel_pipeline pipeline DistilBertForQuestionAnswering from nypgd
+author: John Snow Labs
+name: disitlbert_finetunedmodel_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`disitlbert_finetunedmodel_pipeline` is a English model originally trained by nypgd.
+
+{:.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/disitlbert_finetunedmodel_pipeline_en_5.5.0_3.0_1725868852134.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/disitlbert_finetunedmodel_pipeline_en_5.5.0_3.0_1725868852134.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
+
+pipeline = PretrainedPipeline("disitlbert_finetunedmodel_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("disitlbert_finetunedmodel_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|disitlbert_finetunedmodel_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/nypgd/disitlbert_finetunedmodel
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distilbert_akabot_en.md b/docs/_posts/ahmedlone127/2024-09-09-distilbert_akabot_en.md
new file mode 100644
index 00000000000000..9279744259743a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distilbert_akabot_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_akabot DistilBertForQuestionAnswering from avisena
+author: John Snow Labs
+name: distilbert_akabot
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_akabot` is a English model originally trained by avisena.
+
+{:.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/distilbert_akabot_en_5.5.0_3.0_1725869116259.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_akabot_en_5.5.0_3.0_1725869116259.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_akabot","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_akabot", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_akabot|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/avisena/distilbert_akabot
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_cased_fine_tuned_blbooksgenre_en.md b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_cased_fine_tuned_blbooksgenre_en.md
new file mode 100644
index 00000000000000..c3fb3a9212e8ae
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_cased_fine_tuned_blbooksgenre_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English distilbert_base_cased_fine_tuned_blbooksgenre DistilBertEmbeddings from BritishLibraryLabs
+author: John Snow Labs
+name: distilbert_base_cased_fine_tuned_blbooksgenre
+date: 2024-09-09
+tags: [distilbert, en, open_source, fill_mask, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings  model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_cased_fine_tuned_blbooksgenre` is a English model originally trained by BritishLibraryLabs.
+
+## 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/distilbert_base_cased_fine_tuned_blbooksgenre_en_5.5.0_3.0_1725878056910.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_cased_fine_tuned_blbooksgenre_en_5.5.0_3.0_1725878056910.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 =DistilBertEmbeddings.pretrained("distilbert_base_cased_fine_tuned_blbooksgenre","en") \
+            .setInputCols(["documents","token"]) \
+            .setOutputCol("embeddings")
+
+pipeline = Pipeline().setStages([document_assembler, embeddings])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("embeddings")
+    
+val embeddings = DistilBertEmbeddings 
+    .pretrained("distilbert_base_cased_fine_tuned_blbooksgenre", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("embeddings") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_cased_fine_tuned_blbooksgenre|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|243.7 MB|
+
+## References
+
+References
+
+https://huggingface.co/BritishLibraryLabs/distilbert-base-cased-fine-tuned-blbooksgenre
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_cased_fine_tuned_blbooksgenre_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_cased_fine_tuned_blbooksgenre_pipeline_en.md
new file mode 100644
index 00000000000000..c7000da0dbc73b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_cased_fine_tuned_blbooksgenre_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_cased_fine_tuned_blbooksgenre_pipeline pipeline DistilBertEmbeddings from TheBritishLibrary
+author: John Snow Labs
+name: distilbert_base_cased_fine_tuned_blbooksgenre_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_cased_fine_tuned_blbooksgenre_pipeline` is a English model originally trained by TheBritishLibrary.
+
+{:.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/distilbert_base_cased_fine_tuned_blbooksgenre_pipeline_en_5.5.0_3.0_1725878068648.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_cased_fine_tuned_blbooksgenre_pipeline_en_5.5.0_3.0_1725878068648.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
+
+pipeline = PretrainedPipeline("distilbert_base_cased_fine_tuned_blbooksgenre_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_cased_fine_tuned_blbooksgenre_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_cased_fine_tuned_blbooksgenre_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/TheBritishLibrary/distilbert-base-cased-fine-tuned-blbooksgenre
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_japanese_cased_jaquad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_japanese_cased_jaquad_pipeline_en.md
new file mode 100644
index 00000000000000..5a93288dff7e98
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_japanese_cased_jaquad_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_japanese_cased_jaquad_pipeline pipeline DistilBertForQuestionAnswering from cuongtk2002
+author: John Snow Labs
+name: distilbert_base_japanese_cased_jaquad_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_japanese_cased_jaquad_pipeline` is a English model originally trained by cuongtk2002.
+
+{:.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/distilbert_base_japanese_cased_jaquad_pipeline_en_5.5.0_3.0_1725877328126.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_japanese_cased_jaquad_pipeline_en_5.5.0_3.0_1725877328126.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
+
+pipeline = PretrainedPipeline("distilbert_base_japanese_cased_jaquad_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_japanese_cased_jaquad_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_japanese_cased_jaquad_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|255.1 MB|
+
+## References
+
+https://huggingface.co/cuongtk2002/distilbert-base-ja-cased-JaQuAD
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_clickbait_detection_en.md b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_clickbait_detection_en.md
new file mode 100644
index 00000000000000..541977e9bfb460
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_clickbait_detection_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_clickbait_detection DistilBertForQuestionAnswering from abdulmanaam
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_clickbait_detection
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_clickbait_detection` is a English model originally trained by abdulmanaam.
+
+{:.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/distilbert_base_uncased_finetuned_clickbait_detection_en_5.5.0_3.0_1725877101750.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_clickbait_detection_en_5.5.0_3.0_1725877101750.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_clickbait_detection","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_clickbait_detection", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_clickbait_detection|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/abdulmanaam/distilbert-base-uncased-finetuned-clickbait-detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_clinic_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_clinic_pipeline_en.md
new file mode 100644
index 00000000000000..e80930031a73fc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_clinic_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_clinic_pipeline pipeline DistilBertForSequenceClassification from hndc
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_clinic_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_clinic_pipeline` is a English model originally trained by hndc.
+
+{:.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/distilbert_base_uncased_finetuned_clinic_pipeline_en_5.5.0_3.0_1725873167082.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_clinic_pipeline_en_5.5.0_3.0_1725873167082.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_clinic_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_clinic_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_clinic_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.9 MB|
+
+## References
+
+https://huggingface.co/hndc/distilbert-base-uncased-finetuned-clinic
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_dob_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_dob_pipeline_en.md
new file mode 100644
index 00000000000000..4fdf9f57101543
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_dob_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_dob_pipeline pipeline DistilBertEmbeddings from MattiaParavisi
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_dob_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_dob_pipeline` is a English model originally trained by MattiaParavisi.
+
+{:.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/distilbert_base_uncased_finetuned_dob_pipeline_en_5.5.0_3.0_1725868005348.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_dob_pipeline_en_5.5.0_3.0_1725868005348.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_dob_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_dob_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_dob_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/MattiaParavisi/distilbert-base-uncased-finetuned-dob
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_emotion_saneryi_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_emotion_saneryi_pipeline_en.md
new file mode 100644
index 00000000000000..60aa06461096fd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_emotion_saneryi_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_emotion_saneryi_pipeline pipeline DistilBertForSequenceClassification from Saneryi
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_emotion_saneryi_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_saneryi_pipeline` is a English model originally trained by Saneryi.
+
+{:.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/distilbert_base_uncased_finetuned_emotion_saneryi_pipeline_en_5.5.0_3.0_1725873467437.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_saneryi_pipeline_en_5.5.0_3.0_1725873467437.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_saneryi_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_saneryi_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_emotion_saneryi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/Saneryi/distilbert-base-uncased-finetuned-emotion
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_accelerate_achakr37_en.md b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_accelerate_achakr37_en.md
new file mode 100644
index 00000000000000..fe3d944fdac8eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_accelerate_achakr37_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_accelerate_achakr37 DistilBertEmbeddings from achakr37
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_accelerate_achakr37
+date: 2024-09-09
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_accelerate_achakr37` is a English model originally trained by achakr37.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_accelerate_achakr37_en_5.5.0_3.0_1725878295472.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_accelerate_achakr37_en_5.5.0_3.0_1725878295472.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_accelerate_achakr37","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_accelerate_achakr37","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_accelerate_achakr37|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/achakr37/distilbert-base-uncased-finetuned-imdb-accelerate
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_accelerate_mithegooie_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_accelerate_mithegooie_pipeline_en.md
new file mode 100644
index 00000000000000..d1589d4b1ed297
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_accelerate_mithegooie_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_accelerate_mithegooie_pipeline pipeline DistilBertEmbeddings from mithegooie
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_accelerate_mithegooie_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_accelerate_mithegooie_pipeline` is a English model originally trained by mithegooie.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_accelerate_mithegooie_pipeline_en_5.5.0_3.0_1725868306512.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_accelerate_mithegooie_pipeline_en_5.5.0_3.0_1725868306512.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_accelerate_mithegooie_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_accelerate_mithegooie_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_accelerate_mithegooie_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/mithegooie/distilbert-base-uncased-finetuned-imdb-accelerate
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_accelerate_rezakakooee_en.md b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_accelerate_rezakakooee_en.md
new file mode 100644
index 00000000000000..37c6ec4c2a9c4e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_accelerate_rezakakooee_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_accelerate_rezakakooee DistilBertEmbeddings from Rezakakooee
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_accelerate_rezakakooee
+date: 2024-09-09
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_accelerate_rezakakooee` is a English model originally trained by Rezakakooee.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_accelerate_rezakakooee_en_5.5.0_3.0_1725878109282.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_accelerate_rezakakooee_en_5.5.0_3.0_1725878109282.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_accelerate_rezakakooee","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_accelerate_rezakakooee","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_accelerate_rezakakooee|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Rezakakooee/distilbert-base-uncased-finetuned-imdb-accelerate
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_accelerate_rezakakooee_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_accelerate_rezakakooee_pipeline_en.md
new file mode 100644
index 00000000000000..479e0d205622ff
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_accelerate_rezakakooee_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_accelerate_rezakakooee_pipeline pipeline DistilBertEmbeddings from Rezakakooee
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_accelerate_rezakakooee_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_accelerate_rezakakooee_pipeline` is a English model originally trained by Rezakakooee.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_accelerate_rezakakooee_pipeline_en_5.5.0_3.0_1725878122010.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_accelerate_rezakakooee_pipeline_en_5.5.0_3.0_1725878122010.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_accelerate_rezakakooee_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_accelerate_rezakakooee_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_accelerate_rezakakooee_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Rezakakooee/distilbert-base-uncased-finetuned-imdb-accelerate
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_accelerate_rjomega_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_accelerate_rjomega_pipeline_en.md
new file mode 100644
index 00000000000000..72eeb2ce1d6555
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_accelerate_rjomega_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_accelerate_rjomega_pipeline pipeline DistilBertEmbeddings from rjomega
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_accelerate_rjomega_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_accelerate_rjomega_pipeline` is a English model originally trained by rjomega.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_accelerate_rjomega_pipeline_en_5.5.0_3.0_1725868011981.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_accelerate_rjomega_pipeline_en_5.5.0_3.0_1725868011981.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_accelerate_rjomega_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_accelerate_rjomega_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_accelerate_rjomega_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/rjomega/distilbert-base-uncased-finetuned-imdb-accelerate
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_accelerate_strawhatdrag0n_en.md b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_accelerate_strawhatdrag0n_en.md
new file mode 100644
index 00000000000000..cb57dbb20cea01
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_accelerate_strawhatdrag0n_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_accelerate_strawhatdrag0n DistilBertEmbeddings from StrawHatDrag0n
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_accelerate_strawhatdrag0n
+date: 2024-09-09
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_accelerate_strawhatdrag0n` is a English model originally trained by StrawHatDrag0n.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_accelerate_strawhatdrag0n_en_5.5.0_3.0_1725867832357.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_accelerate_strawhatdrag0n_en_5.5.0_3.0_1725867832357.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_accelerate_strawhatdrag0n","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_accelerate_strawhatdrag0n","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_accelerate_strawhatdrag0n|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/StrawHatDrag0n/distilbert-base-uncased-finetuned-imdb-accelerate
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_accelerate_strawhatdrag0n_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_accelerate_strawhatdrag0n_pipeline_en.md
new file mode 100644
index 00000000000000..b20215cfbaee24
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_accelerate_strawhatdrag0n_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_accelerate_strawhatdrag0n_pipeline pipeline DistilBertEmbeddings from StrawHatDrag0n
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_accelerate_strawhatdrag0n_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_accelerate_strawhatdrag0n_pipeline` is a English model originally trained by StrawHatDrag0n.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_accelerate_strawhatdrag0n_pipeline_en_5.5.0_3.0_1725867843887.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_accelerate_strawhatdrag0n_pipeline_en_5.5.0_3.0_1725867843887.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_accelerate_strawhatdrag0n_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_accelerate_strawhatdrag0n_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_accelerate_strawhatdrag0n_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/StrawHatDrag0n/distilbert-base-uncased-finetuned-imdb-accelerate
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_flavortown_en.md b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_flavortown_en.md
new file mode 100644
index 00000000000000..43c111b235568e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_flavortown_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_flavortown DistilBertEmbeddings from flavortown
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_flavortown
+date: 2024-09-09
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_flavortown` is a English model originally trained by flavortown.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_flavortown_en_5.5.0_3.0_1725867890471.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_flavortown_en_5.5.0_3.0_1725867890471.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_flavortown","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_flavortown","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_flavortown|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/flavortown/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_guydebruyn_en.md b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_guydebruyn_en.md
new file mode 100644
index 00000000000000..6f5e7b5f20c1e9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_guydebruyn_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_guydebruyn DistilBertEmbeddings from guydebruyn
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_guydebruyn
+date: 2024-09-09
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_guydebruyn` is a English model originally trained by guydebruyn.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_guydebruyn_en_5.5.0_3.0_1725878227054.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_guydebruyn_en_5.5.0_3.0_1725878227054.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_guydebruyn","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_guydebruyn","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_guydebruyn|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/guydebruyn/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_janetyu_en.md b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_janetyu_en.md
new file mode 100644
index 00000000000000..113516ec268603
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_janetyu_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_janetyu DistilBertEmbeddings from janetyu
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_janetyu
+date: 2024-09-09
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_janetyu` is a English model originally trained by janetyu.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_janetyu_en_5.5.0_3.0_1725868126369.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_janetyu_en_5.5.0_3.0_1725868126369.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_janetyu","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_janetyu","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_janetyu|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/janetyu/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_janetyu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_janetyu_pipeline_en.md
new file mode 100644
index 00000000000000..49a321200f96f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_janetyu_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_janetyu_pipeline pipeline DistilBertEmbeddings from janetyu
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_janetyu_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_janetyu_pipeline` is a English model originally trained by janetyu.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_janetyu_pipeline_en_5.5.0_3.0_1725868140281.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_janetyu_pipeline_en_5.5.0_3.0_1725868140281.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_janetyu_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_janetyu_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_janetyu_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/janetyu/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_loganathanspr_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_loganathanspr_pipeline_en.md
new file mode 100644
index 00000000000000..22612948be99c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_loganathanspr_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_loganathanspr_pipeline pipeline DistilBertEmbeddings from loganathanspr
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_loganathanspr_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_loganathanspr_pipeline` is a English model originally trained by loganathanspr.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_loganathanspr_pipeline_en_5.5.0_3.0_1725868431725.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_loganathanspr_pipeline_en_5.5.0_3.0_1725868431725.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_loganathanspr_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_loganathanspr_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_loganathanspr_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/loganathanspr/distilbert-base-uncased-finetuned-imdb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_sechmo_en.md b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_sechmo_en.md
new file mode 100644
index 00000000000000..154131a189a7e4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_imdb_sechmo_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_imdb_sechmo DistilBertEmbeddings from sechmo
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_imdb_sechmo
+date: 2024-09-09
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_sechmo` is a English model originally trained by sechmo.
+
+{:.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/distilbert_base_uncased_finetuned_imdb_sechmo_en_5.5.0_3.0_1725877962587.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_sechmo_en_5.5.0_3.0_1725877962587.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_sechmo","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_sechmo","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_imdb_sechmo|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/sechmo/distilbert-base-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_squad_azyren_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_squad_azyren_pipeline_en.md
new file mode 100644
index 00000000000000..e09bf0dd534490
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_squad_azyren_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_azyren_pipeline pipeline DistilBertForQuestionAnswering from Azyren
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_azyren_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_azyren_pipeline` is a English model originally trained by Azyren.
+
+{:.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/distilbert_base_uncased_finetuned_squad_azyren_pipeline_en_5.5.0_3.0_1725877159001.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_azyren_pipeline_en_5.5.0_3.0_1725877159001.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_azyren_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_azyren_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_azyren_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Azyren/distilbert-base-uncased-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_squad_dmlotto_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_squad_dmlotto_pipeline_en.md
new file mode 100644
index 00000000000000..ee3a2cf840bb6f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_squad_dmlotto_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_dmlotto_pipeline pipeline DistilBertForQuestionAnswering from dmlotto
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_dmlotto_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_dmlotto_pipeline` is a English model originally trained by dmlotto.
+
+{:.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/distilbert_base_uncased_finetuned_squad_dmlotto_pipeline_en_5.5.0_3.0_1725869039788.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_dmlotto_pipeline_en_5.5.0_3.0_1725869039788.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_dmlotto_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_dmlotto_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_dmlotto_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/dmlotto/distilbert-base-uncased-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_squad_parthmaheshwari_en.md b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_squad_parthmaheshwari_en.md
new file mode 100644
index 00000000000000..2decfcf599a233
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_squad_parthmaheshwari_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_parthmaheshwari DistilBertForQuestionAnswering from parthmaheshwari
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_parthmaheshwari
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_parthmaheshwari` is a English model originally trained by parthmaheshwari.
+
+{:.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/distilbert_base_uncased_finetuned_squad_parthmaheshwari_en_5.5.0_3.0_1725869218853.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_parthmaheshwari_en_5.5.0_3.0_1725869218853.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_parthmaheshwari","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_parthmaheshwari", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_parthmaheshwari|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/parthmaheshwari/distilbert-base-uncased-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_squad_sachinsingh31_en.md b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_squad_sachinsingh31_en.md
new file mode 100644
index 00000000000000..acad7db59b1a2b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_squad_sachinsingh31_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_sachinsingh31 DistilBertForQuestionAnswering from sachinsingh31
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_sachinsingh31
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_sachinsingh31` is a English model originally trained by sachinsingh31.
+
+{:.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/distilbert_base_uncased_finetuned_squad_sachinsingh31_en_5.5.0_3.0_1725876855994.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_sachinsingh31_en_5.5.0_3.0_1725876855994.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_sachinsingh31","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_sachinsingh31", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_sachinsingh31|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/sachinsingh31/distilbert-base-uncased-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_squad_sachinsingh31_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_squad_sachinsingh31_pipeline_en.md
new file mode 100644
index 00000000000000..37d6bebb6aa101
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distilbert_base_uncased_finetuned_squad_sachinsingh31_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distilbert_base_uncased_finetuned_squad_sachinsingh31_pipeline pipeline DistilBertForQuestionAnswering from sachinsingh31
+author: John Snow Labs
+name: distilbert_base_uncased_finetuned_squad_sachinsingh31_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_sachinsingh31_pipeline` is a English model originally trained by sachinsingh31.
+
+{:.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/distilbert_base_uncased_finetuned_squad_sachinsingh31_pipeline_en_5.5.0_3.0_1725876867208.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_sachinsingh31_pipeline_en_5.5.0_3.0_1725876867208.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
+
+pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_sachinsingh31_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_sachinsingh31_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_base_uncased_finetuned_squad_sachinsingh31_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/sachinsingh31/distilbert-base-uncased-finetuned-squad
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distilbert_beekeeping_qanda_model_en.md b/docs/_posts/ahmedlone127/2024-09-09-distilbert_beekeeping_qanda_model_en.md
new file mode 100644
index 00000000000000..42f1f1bca9fa31
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distilbert_beekeeping_qanda_model_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distilbert_beekeeping_qanda_model DistilBertForQuestionAnswering from juman48
+author: John Snow Labs
+name: distilbert_beekeeping_qanda_model
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_beekeeping_qanda_model` is a English model originally trained by juman48.
+
+{:.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/distilbert_beekeeping_qanda_model_en_5.5.0_3.0_1725877048267.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_beekeeping_qanda_model_en_5.5.0_3.0_1725877048267.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_beekeeping_qanda_model","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_beekeeping_qanda_model", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_beekeeping_qanda_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/juman48/distilbert_beekeeping_QandA_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distilbert_qa_flat_N_max_en.md b/docs/_posts/ahmedlone127/2024-09-09-distilbert_qa_flat_N_max_en.md
new file mode 100644
index 00000000000000..a899aaf56d6030
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distilbert_qa_flat_N_max_en.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: English DistilBertForQuestionAnswering model (from mcurmei) Flat
+author: John Snow Labs
+name: distilbert_qa_flat_N_max
+date: 2024-09-09
+tags: [en, open_source, distilbert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `flat_N_max` is a English model originally trained by `mcurmei`.
+
+## 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/distilbert_qa_flat_N_max_en_5.5.0_3.0_1725869389904.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_qa_flat_N_max_en_5.5.0_3.0_1725869389904.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
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_qa_flat_N_max","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = DistilBertForQuestionAnswering.pretrained("distilbert_qa_flat_N_max","en") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.distil_bert.flat_n_max.by_mcurmei").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_qa_flat_N_max|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+References
+
+- https://huggingface.co/mcurmei/flat_N_max
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distilbert_static_malware_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-distilbert_static_malware_detection_pipeline_en.md
new file mode 100644
index 00000000000000..3dd2f6232e9019
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distilbert_static_malware_detection_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English distilbert_static_malware_detection_pipeline pipeline DistilBertForSequenceClassification from sibumi
+author: John Snow Labs
+name: distilbert_static_malware_detection_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_static_malware_detection_pipeline` is a English model originally trained by sibumi.
+
+{:.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/distilbert_static_malware_detection_pipeline_en_5.5.0_3.0_1725872974545.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_static_malware_detection_pipeline_en_5.5.0_3.0_1725872974545.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
+
+pipeline = PretrainedPipeline("distilbert_static_malware_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distilbert_static_malware_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distilbert_static_malware_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/sibumi/DISTILBERT_static_malware-detection
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distill_whisper_thai_medium_bjak_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-distill_whisper_thai_medium_bjak_pipeline_en.md
new file mode 100644
index 00000000000000..7776ecd79d30dc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distill_whisper_thai_medium_bjak_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English distill_whisper_thai_medium_bjak_pipeline pipeline WhisperForCTC from bjak
+author: John Snow Labs
+name: distill_whisper_thai_medium_bjak_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distill_whisper_thai_medium_bjak_pipeline` is a English model originally trained by bjak.
+
+{:.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/distill_whisper_thai_medium_bjak_pipeline_en_5.5.0_3.0_1725843975427.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distill_whisper_thai_medium_bjak_pipeline_en_5.5.0_3.0_1725843975427.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
+
+pipeline = PretrainedPipeline("distill_whisper_thai_medium_bjak_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("distill_whisper_thai_medium_bjak_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distill_whisper_thai_medium_bjak_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.0 GB|
+
+## References
+
+https://huggingface.co/bjak/distill-whisper-th-medium
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distillbert_base_spanish_uncased_finetuned_imdb_en.md b/docs/_posts/ahmedlone127/2024-09-09-distillbert_base_spanish_uncased_finetuned_imdb_en.md
new file mode 100644
index 00000000000000..da03a455a57e56
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distillbert_base_spanish_uncased_finetuned_imdb_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English distillbert_base_spanish_uncased_finetuned_imdb DistilBertEmbeddings from franfram
+author: John Snow Labs
+name: distillbert_base_spanish_uncased_finetuned_imdb
+date: 2024-09-09
+tags: [distilbert, en, open_source, fill_mask, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings  model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distillbert_base_spanish_uncased_finetuned_imdb` is a English model originally trained by franfram.
+
+## 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/distillbert_base_spanish_uncased_finetuned_imdb_en_5.5.0_3.0_1725877998959.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distillbert_base_spanish_uncased_finetuned_imdb_en_5.5.0_3.0_1725877998959.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 =DistilBertEmbeddings.pretrained("distillbert_base_spanish_uncased_finetuned_imdb","en") \
+            .setInputCols(["documents","token"]) \
+            .setOutputCol("embeddings")
+
+pipeline = Pipeline().setStages([document_assembler, embeddings])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("embeddings")
+    
+val embeddings = DistilBertEmbeddings 
+    .pretrained("distillbert_base_spanish_uncased_finetuned_imdb", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("embeddings") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distillbert_base_spanish_uncased_finetuned_imdb|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|250.2 MB|
+
+## References
+
+References
+
+https://huggingface.co/franfram/distillbert-base-spanish-uncased-finetuned-imdb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-distiltesttodelete_en.md b/docs/_posts/ahmedlone127/2024-09-09-distiltesttodelete_en.md
new file mode 100644
index 00000000000000..7f05e7300c2024
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-distiltesttodelete_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English distiltesttodelete DistilBertForQuestionAnswering from adamfendri
+author: John Snow Labs
+name: distiltesttodelete
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distiltesttodelete` is a English model originally trained by adamfendri.
+
+{:.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/distiltesttodelete_en_5.5.0_3.0_1725877055040.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distiltesttodelete_en_5.5.0_3.0_1725877055040.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("distiltesttodelete","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("distiltesttodelete", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|distiltesttodelete|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/adamfendri/distilTestToDelete
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-dummy_model_ahamed121_en.md b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_ahamed121_en.md
new file mode 100644
index 00000000000000..e28a112ed586da
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_ahamed121_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_ahamed121 CamemBertEmbeddings from Ahamed121
+author: John Snow Labs
+name: dummy_model_ahamed121
+date: 2024-09-09
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_ahamed121` is a English model originally trained by Ahamed121.
+
+{:.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/dummy_model_ahamed121_en_5.5.0_3.0_1725851578349.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_ahamed121_en_5.5.0_3.0_1725851578349.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_ahamed121","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_ahamed121","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_ahamed121|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Ahamed121/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-dummy_model_airhaohan_en.md b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_airhaohan_en.md
new file mode 100644
index 00000000000000..e7870b3822d16c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_airhaohan_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_airhaohan CamemBertEmbeddings from airhaohan
+author: John Snow Labs
+name: dummy_model_airhaohan
+date: 2024-09-09
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_airhaohan` is a English model originally trained by airhaohan.
+
+{:.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/dummy_model_airhaohan_en_5.5.0_3.0_1725852295135.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_airhaohan_en_5.5.0_3.0_1725852295135.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_airhaohan","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_airhaohan","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_airhaohan|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/airhaohan/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-dummy_model_airhaohan_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_airhaohan_pipeline_en.md
new file mode 100644
index 00000000000000..099d98c4a56a38
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_airhaohan_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_airhaohan_pipeline pipeline CamemBertEmbeddings from airhaohan
+author: John Snow Labs
+name: dummy_model_airhaohan_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_airhaohan_pipeline` is a English model originally trained by airhaohan.
+
+{:.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/dummy_model_airhaohan_pipeline_en_5.5.0_3.0_1725852368924.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_airhaohan_pipeline_en_5.5.0_3.0_1725852368924.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
+
+pipeline = PretrainedPipeline("dummy_model_airhaohan_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_airhaohan_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_airhaohan_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/airhaohan/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-dummy_model_cori00_en.md b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_cori00_en.md
new file mode 100644
index 00000000000000..185c9523396b1e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_cori00_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_cori00 CamemBertEmbeddings from cori00
+author: John Snow Labs
+name: dummy_model_cori00
+date: 2024-09-09
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_cori00` is a English model originally trained by cori00.
+
+{:.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/dummy_model_cori00_en_5.5.0_3.0_1725851901309.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_cori00_en_5.5.0_3.0_1725851901309.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_cori00","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_cori00","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_cori00|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/cori00/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-dummy_model_cori00_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_cori00_pipeline_en.md
new file mode 100644
index 00000000000000..dc311155f53aaa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_cori00_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_cori00_pipeline pipeline CamemBertEmbeddings from cori00
+author: John Snow Labs
+name: dummy_model_cori00_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_cori00_pipeline` is a English model originally trained by cori00.
+
+{:.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/dummy_model_cori00_pipeline_en_5.5.0_3.0_1725851977976.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_cori00_pipeline_en_5.5.0_3.0_1725851977976.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
+
+pipeline = PretrainedPipeline("dummy_model_cori00_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_cori00_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_cori00_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/cori00/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-dummy_model_deepansh09_en.md b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_deepansh09_en.md
new file mode 100644
index 00000000000000..21d563b0bad988
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_deepansh09_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_deepansh09 CamemBertEmbeddings from deepansh09
+author: John Snow Labs
+name: dummy_model_deepansh09
+date: 2024-09-09
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_deepansh09` is a English model originally trained by deepansh09.
+
+{:.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/dummy_model_deepansh09_en_5.5.0_3.0_1725851515233.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_deepansh09_en_5.5.0_3.0_1725851515233.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_deepansh09","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_deepansh09","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_deepansh09|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/deepansh09/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-dummy_model_ericchu000_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_ericchu000_pipeline_en.md
new file mode 100644
index 00000000000000..5821163afdc8ca
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_ericchu000_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_ericchu000_pipeline pipeline CamemBertEmbeddings from ericchu000
+author: John Snow Labs
+name: dummy_model_ericchu000_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_ericchu000_pipeline` is a English model originally trained by ericchu000.
+
+{:.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/dummy_model_ericchu000_pipeline_en_5.5.0_3.0_1725852208424.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_ericchu000_pipeline_en_5.5.0_3.0_1725852208424.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
+
+pipeline = PretrainedPipeline("dummy_model_ericchu000_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_ericchu000_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_ericchu000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/ericchu000/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-dummy_model_handsomejack42_en.md b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_handsomejack42_en.md
new file mode 100644
index 00000000000000..a16370374e4801
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_handsomejack42_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_handsomejack42 CamemBertEmbeddings from handsomejack42
+author: John Snow Labs
+name: dummy_model_handsomejack42
+date: 2024-09-09
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_handsomejack42` is a English model originally trained by handsomejack42.
+
+{:.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/dummy_model_handsomejack42_en_5.5.0_3.0_1725851756672.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_handsomejack42_en_5.5.0_3.0_1725851756672.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_handsomejack42","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_handsomejack42","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_handsomejack42|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/handsomejack42/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-dummy_model_insub_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_insub_pipeline_en.md
new file mode 100644
index 00000000000000..6f9ef471e8830d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_insub_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_insub_pipeline pipeline CamemBertEmbeddings from insub
+author: John Snow Labs
+name: dummy_model_insub_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_insub_pipeline` is a English model originally trained by insub.
+
+{:.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/dummy_model_insub_pipeline_en_5.5.0_3.0_1725851849755.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_insub_pipeline_en_5.5.0_3.0_1725851849755.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
+
+pipeline = PretrainedPipeline("dummy_model_insub_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_insub_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_insub_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/insub/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-dummy_model_jbao8899_en.md b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_jbao8899_en.md
new file mode 100644
index 00000000000000..4087182cf755e5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_jbao8899_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_jbao8899 CamemBertEmbeddings from jbao8899
+author: John Snow Labs
+name: dummy_model_jbao8899
+date: 2024-09-09
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jbao8899` is a English model originally trained by jbao8899.
+
+{:.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/dummy_model_jbao8899_en_5.5.0_3.0_1725852149065.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jbao8899_en_5.5.0_3.0_1725852149065.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_jbao8899","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_jbao8899","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_jbao8899|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/jbao8899/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-dummy_model_khanhtq2802_en.md b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_khanhtq2802_en.md
new file mode 100644
index 00000000000000..5b6f42751c1b39
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_khanhtq2802_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_khanhtq2802 CamemBertEmbeddings from khanhtq2802
+author: John Snow Labs
+name: dummy_model_khanhtq2802
+date: 2024-09-09
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_khanhtq2802` is a English model originally trained by khanhtq2802.
+
+{:.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/dummy_model_khanhtq2802_en_5.5.0_3.0_1725851543946.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_khanhtq2802_en_5.5.0_3.0_1725851543946.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_khanhtq2802","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_khanhtq2802","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_khanhtq2802|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/khanhtq2802/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-dummy_model_khanhtq2802_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_khanhtq2802_pipeline_en.md
new file mode 100644
index 00000000000000..a035b6e80bdc6e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_khanhtq2802_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_khanhtq2802_pipeline pipeline CamemBertEmbeddings from khanhtq2802
+author: John Snow Labs
+name: dummy_model_khanhtq2802_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_khanhtq2802_pipeline` is a English model originally trained by khanhtq2802.
+
+{:.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/dummy_model_khanhtq2802_pipeline_en_5.5.0_3.0_1725851619465.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_khanhtq2802_pipeline_en_5.5.0_3.0_1725851619465.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
+
+pipeline = PretrainedPipeline("dummy_model_khanhtq2802_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_khanhtq2802_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_khanhtq2802_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/khanhtq2802/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-dummy_model_terps_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_terps_pipeline_en.md
new file mode 100644
index 00000000000000..d673b7da6985b4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_terps_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_terps_pipeline pipeline CamemBertEmbeddings from Terps
+author: John Snow Labs
+name: dummy_model_terps_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_terps_pipeline` is a English model originally trained by Terps.
+
+{:.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/dummy_model_terps_pipeline_en_5.5.0_3.0_1725852092808.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_terps_pipeline_en_5.5.0_3.0_1725852092808.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
+
+pipeline = PretrainedPipeline("dummy_model_terps_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_terps_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_terps_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Terps/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-dummy_model_verfallen_en.md b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_verfallen_en.md
new file mode 100644
index 00000000000000..8fa9fef18a9189
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_verfallen_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_verfallen CamemBertEmbeddings from verfallen
+author: John Snow Labs
+name: dummy_model_verfallen
+date: 2024-09-09
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_verfallen` is a English model originally trained by verfallen.
+
+{:.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/dummy_model_verfallen_en_5.5.0_3.0_1725851212877.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_verfallen_en_5.5.0_3.0_1725851212877.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_verfallen","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_verfallen","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_verfallen|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/verfallen/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-dummy_model_vn240923_en.md b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_vn240923_en.md
new file mode 100644
index 00000000000000..1317ed13c6ea6f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_vn240923_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_vn240923 CamemBertEmbeddings from anhtn
+author: John Snow Labs
+name: dummy_model_vn240923
+date: 2024-09-09
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_vn240923` is a English model originally trained by anhtn.
+
+{:.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/dummy_model_vn240923_en_5.5.0_3.0_1725851212970.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_vn240923_en_5.5.0_3.0_1725851212970.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_vn240923","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_vn240923","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_vn240923|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/anhtn/dummy-model-vn240923
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-dummy_model_weipeng_en.md b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_weipeng_en.md
new file mode 100644
index 00000000000000..b89f37806d86b5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_weipeng_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_model_weipeng CamemBertEmbeddings from Weipeng
+author: John Snow Labs
+name: dummy_model_weipeng
+date: 2024-09-09
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_weipeng` is a English model originally trained by Weipeng.
+
+{:.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/dummy_model_weipeng_en_5.5.0_3.0_1725852246685.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_weipeng_en_5.5.0_3.0_1725852246685.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_model_weipeng","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_model_weipeng","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_weipeng|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Weipeng/dummy-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-dummy_model_weipeng_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_weipeng_pipeline_en.md
new file mode 100644
index 00000000000000..b15e45029930b9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_weipeng_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_model_weipeng_pipeline pipeline CamemBertEmbeddings from Weipeng
+author: John Snow Labs
+name: dummy_model_weipeng_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_weipeng_pipeline` is a English model originally trained by Weipeng.
+
+{:.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/dummy_model_weipeng_pipeline_en_5.5.0_3.0_1725852321398.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_weipeng_pipeline_en_5.5.0_3.0_1725852321398.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
+
+pipeline = PretrainedPipeline("dummy_model_weipeng_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_model_weipeng_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_model_weipeng_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/Weipeng/dummy-model
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-dummy_nirmeshdell_en.md b/docs/_posts/ahmedlone127/2024-09-09-dummy_nirmeshdell_en.md
new file mode 100644
index 00000000000000..1ec16a6a5d817c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-dummy_nirmeshdell_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English dummy_nirmeshdell CamemBertEmbeddings from nirmeshdell
+author: John Snow Labs
+name: dummy_nirmeshdell
+date: 2024-09-09
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_nirmeshdell` is a English model originally trained by nirmeshdell.
+
+{:.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/dummy_nirmeshdell_en_5.5.0_3.0_1725851443515.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_nirmeshdell_en_5.5.0_3.0_1725851443515.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("dummy_nirmeshdell","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("dummy_nirmeshdell","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_nirmeshdell|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/nirmeshdell/dummy
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-dummy_nirmeshdell_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-dummy_nirmeshdell_pipeline_en.md
new file mode 100644
index 00000000000000..489ad0eb16d843
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-dummy_nirmeshdell_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_nirmeshdell_pipeline pipeline CamemBertEmbeddings from nirmeshdell
+author: John Snow Labs
+name: dummy_nirmeshdell_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_nirmeshdell_pipeline` is a English model originally trained by nirmeshdell.
+
+{:.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/dummy_nirmeshdell_pipeline_en_5.5.0_3.0_1725851520009.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_nirmeshdell_pipeline_en_5.5.0_3.0_1725851520009.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
+
+pipeline = PretrainedPipeline("dummy_nirmeshdell_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_nirmeshdell_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_nirmeshdell_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/nirmeshdell/dummy
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-dummy_ryo1443_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-dummy_ryo1443_pipeline_en.md
new file mode 100644
index 00000000000000..b59ecfcaa80d95
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-dummy_ryo1443_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English dummy_ryo1443_pipeline pipeline CamemBertEmbeddings from ryo1443
+author: John Snow Labs
+name: dummy_ryo1443_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_ryo1443_pipeline` is a English model originally trained by ryo1443.
+
+{:.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/dummy_ryo1443_pipeline_en_5.5.0_3.0_1725852095487.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_ryo1443_pipeline_en_5.5.0_3.0_1725852095487.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
+
+pipeline = PretrainedPipeline("dummy_ryo1443_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("dummy_ryo1443_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dummy_ryo1443_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/ryo1443/dummy
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-dzoqamodel_en.md b/docs/_posts/ahmedlone127/2024-09-09-dzoqamodel_en.md
new file mode 100644
index 00000000000000..c04f6c97972fbb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-dzoqamodel_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English dzoqamodel RoBertaForQuestionAnswering from Norphel
+author: John Snow Labs
+name: dzoqamodel
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dzoqamodel` is a English model originally trained by Norphel.
+
+{:.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/dzoqamodel_en_5.5.0_3.0_1725876679716.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dzoqamodel_en_5.5.0_3.0_1725876679716.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("dzoqamodel","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("dzoqamodel", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|dzoqamodel|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|311.2 MB|
+
+## References
+
+https://huggingface.co/Norphel/dzoQAmodel
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-electra_embeddings_delectra_generator_ko.md b/docs/_posts/ahmedlone127/2024-09-09-electra_embeddings_delectra_generator_ko.md
new file mode 100644
index 00000000000000..025ad28806d4be
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-electra_embeddings_delectra_generator_ko.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: Korean Electra Embeddings (from deeq)
+author: John Snow Labs
+name: electra_embeddings_delectra_generator
+date: 2024-09-09
+tags: [ko, open_source, electra, embeddings, onnx]
+task: Embeddings
+language: ko
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Electra Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `delectra-generator` is a Korean model orginally trained by `deeq`.
+
+## 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/electra_embeddings_delectra_generator_ko_5.5.0_3.0_1725882277673.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_embeddings_delectra_generator_ko_5.5.0_3.0_1725882277673.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
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("document")
+
+tokenizer = Tokenizer() \
+    .setInputCols("document") \
+    .setOutputCol("token")
+  
+embeddings = BertEmbeddings.pretrained("electra_embeddings_delectra_generator","ko") \
+    .setInputCols(["document", "token"]) \
+    .setOutputCol("embeddings")
+    
+pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings])
+
+data = spark.createDataFrame([["나는 Spark NLP를 좋아합니다"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+      .setInputCol("text") 
+      .setOutputCol("document")
+ 
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("electra_embeddings_delectra_generator","ko") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+
+val data = Seq("나는 Spark NLP를 좋아합니다").toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_embeddings_delectra_generator|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|ko|
+|Size:|138.7 MB|
+
+## References
+
+References
+
+- https://huggingface.co/deeq/delectra-generator
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-electra_qa_base_discriminator_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2024-09-09-electra_qa_base_discriminator_finetuned_squad_en.md
new file mode 100644
index 00000000000000..71c9edc95cd4ec
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-electra_qa_base_discriminator_finetuned_squad_en.md
@@ -0,0 +1,98 @@
+---
+layout: model
+title: English ElectraForQuestionAnswering model (from usami)
+author: John Snow Labs
+name: electra_qa_base_discriminator_finetuned_squad
+date: 2024-09-09
+tags: [en, open_source, electra, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `electra-base-discriminator-finetuned-squad` is a English model originally trained by `usami`.
+
+## 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/electra_qa_base_discriminator_finetuned_squad_en_5.5.0_3.0_1725886254853.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/electra_qa_base_discriminator_finetuned_squad_en_5.5.0_3.0_1725886254853.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
+documentAssembler = MultiDocumentAssembler() \
+.setInputCols(["question", "context"]) \
+.setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("electra_qa_base_discriminator_finetuned_squad","en") \
+.setInputCols(["document_question", "document_context"]) \
+.setOutputCol("answer")\
+.setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+.setInputCols(Array("question", "context")) 
+.setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("electra_qa_base_discriminator_finetuned_squad","en") 
+.setInputCols(Array("document", "token")) 
+.setOutputCol("answer")
+.setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.squad.electra.base").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|electra_qa_base_discriminator_finetuned_squad|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|408.0 MB|
+
+## References
+
+References
+
+- https://huggingface.co/usami/electra-base-discriminator-finetuned-squad
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-ellis_qa_en.md b/docs/_posts/ahmedlone127/2024-09-09-ellis_qa_en.md
new file mode 100644
index 00000000000000..7c98113426da2a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-ellis_qa_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English ellis_qa RoBertaForQuestionAnswering from gsl22
+author: John Snow Labs
+name: ellis_qa
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ellis_qa` is a English model originally trained by gsl22.
+
+{:.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/ellis_qa_en_5.5.0_3.0_1725876495543.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ellis_qa_en_5.5.0_3.0_1725876495543.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("ellis_qa","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("ellis_qa", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ellis_qa|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|463.5 MB|
+
+## References
+
+https://huggingface.co/gsl22/Ellis-QA
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-esci_us_base_mpnet_crossencoder_en.md b/docs/_posts/ahmedlone127/2024-09-09-esci_us_base_mpnet_crossencoder_en.md
new file mode 100644
index 00000000000000..08ecf46a88da59
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-esci_us_base_mpnet_crossencoder_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English esci_us_base_mpnet_crossencoder MPNetForSequenceClassification from spacemanidol
+author: John Snow Labs
+name: esci_us_base_mpnet_crossencoder
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, mpnet]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`esci_us_base_mpnet_crossencoder` is a English model originally trained by spacemanidol.
+
+{:.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/esci_us_base_mpnet_crossencoder_en_5.5.0_3.0_1725850708006.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esci_us_base_mpnet_crossencoder_en_5.5.0_3.0_1725850708006.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = MPNetForSequenceClassification.pretrained("esci_us_base_mpnet_crossencoder","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = MPNetForSequenceClassification.pretrained("esci_us_base_mpnet_crossencoder", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|esci_us_base_mpnet_crossencoder|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|407.4 MB|
+
+## References
+
+https://huggingface.co/spacemanidol/esci-us-base-mpnet-crossencoder
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-exalt_baseline_en.md b/docs/_posts/ahmedlone127/2024-09-09-exalt_baseline_en.md
new file mode 100644
index 00000000000000..d6028017b28827
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-exalt_baseline_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English exalt_baseline XlmRoBertaForSequenceClassification from pranaydeeps
+author: John Snow Labs
+name: exalt_baseline
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`exalt_baseline` is a English model originally trained by pranaydeeps.
+
+{:.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/exalt_baseline_en_5.5.0_3.0_1725871098004.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/exalt_baseline_en_5.5.0_3.0_1725871098004.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("exalt_baseline","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("exalt_baseline", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|exalt_baseline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|835.5 MB|
+
+## References
+
+https://huggingface.co/pranaydeeps/EXALT-Baseline
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-facets_gpt_1234_en.md b/docs/_posts/ahmedlone127/2024-09-09-facets_gpt_1234_en.md
new file mode 100644
index 00000000000000..5d22d042dd962a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-facets_gpt_1234_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English facets_gpt_1234 MPNetEmbeddings from ingeol
+author: John Snow Labs
+name: facets_gpt_1234
+date: 2024-09-09
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`facets_gpt_1234` is a English model originally trained by ingeol.
+
+{:.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/facets_gpt_1234_en_5.5.0_3.0_1725874790903.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/facets_gpt_1234_en_5.5.0_3.0_1725874790903.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("facets_gpt_1234","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("facets_gpt_1234","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|facets_gpt_1234|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/ingeol/facets_gpt_1234
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-fine_tuned_deberta_category_by_notes_synthetic_en.md b/docs/_posts/ahmedlone127/2024-09-09-fine_tuned_deberta_category_by_notes_synthetic_en.md
new file mode 100644
index 00000000000000..54f999d064c290
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-fine_tuned_deberta_category_by_notes_synthetic_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English fine_tuned_deberta_category_by_notes_synthetic DeBertaForSequenceClassification from adhityaprimandhika
+author: John Snow Labs
+name: fine_tuned_deberta_category_by_notes_synthetic
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_deberta_category_by_notes_synthetic` is a English model originally trained by adhityaprimandhika.
+
+{:.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/fine_tuned_deberta_category_by_notes_synthetic_en_5.5.0_3.0_1725880154377.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_deberta_category_by_notes_synthetic_en_5.5.0_3.0_1725880154377.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("fine_tuned_deberta_category_by_notes_synthetic","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("fine_tuned_deberta_category_by_notes_synthetic", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_deberta_category_by_notes_synthetic|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/adhityaprimandhika/fine-tuned-deberta-category-by-notes-synthetic
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-fine_tuned_deberta_category_by_notes_synthetic_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-fine_tuned_deberta_category_by_notes_synthetic_pipeline_en.md
new file mode 100644
index 00000000000000..cabfffe5c8de07
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-fine_tuned_deberta_category_by_notes_synthetic_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English fine_tuned_deberta_category_by_notes_synthetic_pipeline pipeline DeBertaForSequenceClassification from adhityaprimandhika
+author: John Snow Labs
+name: fine_tuned_deberta_category_by_notes_synthetic_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_deberta_category_by_notes_synthetic_pipeline` is a English model originally trained by adhityaprimandhika.
+
+{:.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/fine_tuned_deberta_category_by_notes_synthetic_pipeline_en_5.5.0_3.0_1725880275032.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_deberta_category_by_notes_synthetic_pipeline_en_5.5.0_3.0_1725880275032.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
+
+pipeline = PretrainedPipeline("fine_tuned_deberta_category_by_notes_synthetic_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("fine_tuned_deberta_category_by_notes_synthetic_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|fine_tuned_deberta_category_by_notes_synthetic_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/adhityaprimandhika/fine-tuned-deberta-category-by-notes-synthetic
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-finetuned_cont_en.md b/docs/_posts/ahmedlone127/2024-09-09-finetuned_cont_en.md
new file mode 100644
index 00000000000000..7123c3388846d6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-finetuned_cont_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English finetuned_cont AlbertForSequenceClassification from PoptropicaSahil
+author: John Snow Labs
+name: finetuned_cont
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, albert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: AlbertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_cont` is a English model originally trained by PoptropicaSahil.
+
+{:.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/finetuned_cont_en_5.5.0_3.0_1725853920705.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_cont_en_5.5.0_3.0_1725853920705.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = AlbertForSequenceClassification.pretrained("finetuned_cont","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = AlbertForSequenceClassification.pretrained("finetuned_cont", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_cont|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|127.7 MB|
+
+## References
+
+https://huggingface.co/PoptropicaSahil/finetuned_cont
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-finetuned_marianmtmodel_specialfrom_ccmatrix77k_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-finetuned_marianmtmodel_specialfrom_ccmatrix77k_pipeline_en.md
new file mode 100644
index 00000000000000..2844c80fc56977
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-finetuned_marianmtmodel_specialfrom_ccmatrix77k_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuned_marianmtmodel_specialfrom_ccmatrix77k_pipeline pipeline MarianTransformer from HugginJake
+author: John Snow Labs
+name: finetuned_marianmtmodel_specialfrom_ccmatrix77k_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_marianmtmodel_specialfrom_ccmatrix77k_pipeline` is a English model originally trained by HugginJake.
+
+{:.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/finetuned_marianmtmodel_specialfrom_ccmatrix77k_pipeline_en_5.5.0_3.0_1725840313245.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_marianmtmodel_specialfrom_ccmatrix77k_pipeline_en_5.5.0_3.0_1725840313245.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
+
+pipeline = PretrainedPipeline("finetuned_marianmtmodel_specialfrom_ccmatrix77k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_marianmtmodel_specialfrom_ccmatrix77k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_marianmtmodel_specialfrom_ccmatrix77k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|510.1 MB|
+
+## References
+
+https://huggingface.co/HugginJake/Finetuned_MarianMTModel_specialFrom_ccmatrix77k
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-finetuned_random6_3epochs_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-finetuned_random6_3epochs_pipeline_en.md
new file mode 100644
index 00000000000000..50fe3bf7c13415
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-finetuned_random6_3epochs_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English finetuned_random6_3epochs_pipeline pipeline MPNetEmbeddings from jhsmith
+author: John Snow Labs
+name: finetuned_random6_3epochs_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_random6_3epochs_pipeline` is a English model originally trained by jhsmith.
+
+{:.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/finetuned_random6_3epochs_pipeline_en_5.5.0_3.0_1725875123812.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_random6_3epochs_pipeline_en_5.5.0_3.0_1725875123812.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
+
+pipeline = PretrainedPipeline("finetuned_random6_3epochs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuned_random6_3epochs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuned_random6_3epochs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.4 MB|
+
+## References
+
+https://huggingface.co/jhsmith/finetuned_random6_3epochs
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-finetuning_sentiment_model_3000_samples_navazpv_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-finetuning_sentiment_model_3000_samples_navazpv_pipeline_en.md
new file mode 100644
index 00000000000000..d9fa7bfb97d1a6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-finetuning_sentiment_model_3000_samples_navazpv_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English finetuning_sentiment_model_3000_samples_navazpv_pipeline pipeline DistilBertForSequenceClassification from navazpv
+author: John Snow Labs
+name: finetuning_sentiment_model_3000_samples_navazpv_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_navazpv_pipeline` is a English model originally trained by navazpv.
+
+{:.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/finetuning_sentiment_model_3000_samples_navazpv_pipeline_en_5.5.0_3.0_1725872865109.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_navazpv_pipeline_en_5.5.0_3.0_1725872865109.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
+
+pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_samples_navazpv_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_samples_navazpv_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|finetuning_sentiment_model_3000_samples_navazpv_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|249.5 MB|
+
+## References
+
+https://huggingface.co/navazpv/finetuning-sentiment-model-3000-samples
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-furina_seed42_eng_amh_hau_basic_0_0001_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-furina_seed42_eng_amh_hau_basic_0_0001_pipeline_en.md
new file mode 100644
index 00000000000000..56e446b1125476
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-furina_seed42_eng_amh_hau_basic_0_0001_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English furina_seed42_eng_amh_hau_basic_0_0001_pipeline pipeline XlmRoBertaForSequenceClassification from Shijia
+author: John Snow Labs
+name: furina_seed42_eng_amh_hau_basic_0_0001_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`furina_seed42_eng_amh_hau_basic_0_0001_pipeline` is a English model originally trained by Shijia.
+
+{:.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/furina_seed42_eng_amh_hau_basic_0_0001_pipeline_en_5.5.0_3.0_1725870866686.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/furina_seed42_eng_amh_hau_basic_0_0001_pipeline_en_5.5.0_3.0_1725870866686.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
+
+pipeline = PretrainedPipeline("furina_seed42_eng_amh_hau_basic_0_0001_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("furina_seed42_eng_amh_hau_basic_0_0001_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|furina_seed42_eng_amh_hau_basic_0_0001_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/Shijia/furina_seed42_eng_amh_hau_basic_0.0001
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-gefs_language_detector_en.md b/docs/_posts/ahmedlone127/2024-09-09-gefs_language_detector_en.md
new file mode 100644
index 00000000000000..1d64b5fa9fe26f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-gefs_language_detector_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English gefs_language_detector XlmRoBertaForSequenceClassification from ImranzamanML
+author: John Snow Labs
+name: gefs_language_detector
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gefs_language_detector` is a English model originally trained by ImranzamanML.
+
+{:.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/gefs_language_detector_en_5.5.0_3.0_1725871645790.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gefs_language_detector_en_5.5.0_3.0_1725871645790.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("gefs_language_detector","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("gefs_language_detector", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gefs_language_detector|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|805.2 MB|
+
+## References
+
+https://huggingface.co/ImranzamanML/GEFS-language-detector
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-glaswegian_asr_en.md b/docs/_posts/ahmedlone127/2024-09-09-glaswegian_asr_en.md
new file mode 100644
index 00000000000000..d61115cecf156a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-glaswegian_asr_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English glaswegian_asr WhisperForCTC from divakaivan
+author: John Snow Labs
+name: glaswegian_asr
+date: 2024-09-09
+tags: [en, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`glaswegian_asr` is a English model originally trained by divakaivan.
+
+{:.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/glaswegian_asr_en_5.5.0_3.0_1725842143270.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/glaswegian_asr_en_5.5.0_3.0_1725842143270.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
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("glaswegian_asr","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("glaswegian_asr", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|glaswegian_asr|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/divakaivan/glaswegian-asr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-gqa_roberta_german_legal_squad_1000_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-09-gqa_roberta_german_legal_squad_1000_pipeline_de.md
new file mode 100644
index 00000000000000..a752527797f3a4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-gqa_roberta_german_legal_squad_1000_pipeline_de.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: German gqa_roberta_german_legal_squad_1000_pipeline pipeline RoBertaForQuestionAnswering from farid1088
+author: John Snow Labs
+name: gqa_roberta_german_legal_squad_1000_pipeline
+date: 2024-09-09
+tags: [de, open_source, pipeline, onnx]
+task: Question Answering
+language: de
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gqa_roberta_german_legal_squad_1000_pipeline` is a German model originally trained by farid1088.
+
+{:.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/gqa_roberta_german_legal_squad_1000_pipeline_de_5.5.0_3.0_1725867538300.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gqa_roberta_german_legal_squad_1000_pipeline_de_5.5.0_3.0_1725867538300.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
+
+pipeline = PretrainedPipeline("gqa_roberta_german_legal_squad_1000_pipeline", lang = "de")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("gqa_roberta_german_legal_squad_1000_pipeline", lang = "de")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|gqa_roberta_german_legal_squad_1000_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|de|
+|Size:|465.8 MB|
+
+## References
+
+https://huggingface.co/farid1088/GQA_RoBERTa_German_legal_SQuAD_1000
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-hello_english_hindi_translate_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-hello_english_hindi_translate_1_pipeline_en.md
new file mode 100644
index 00000000000000..931ced67997719
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-hello_english_hindi_translate_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English hello_english_hindi_translate_1_pipeline pipeline MarianTransformer from Sarthak7777
+author: John Snow Labs
+name: hello_english_hindi_translate_1_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hello_english_hindi_translate_1_pipeline` is a English model originally trained by Sarthak7777.
+
+{:.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/hello_english_hindi_translate_1_pipeline_en_5.5.0_3.0_1725864450386.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hello_english_hindi_translate_1_pipeline_en_5.5.0_3.0_1725864450386.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
+
+pipeline = PretrainedPipeline("hello_english_hindi_translate_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hello_english_hindi_translate_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hello_english_hindi_translate_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|523.6 MB|
+
+## References
+
+https://huggingface.co/Sarthak7777/hello_en_hi_translate-1
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-helsinki_nlp_finetuned_russian_tonga_tonga_islands_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-helsinki_nlp_finetuned_russian_tonga_tonga_islands_english_pipeline_en.md
new file mode 100644
index 00000000000000..1e23383fc1e5ab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-helsinki_nlp_finetuned_russian_tonga_tonga_islands_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English helsinki_nlp_finetuned_russian_tonga_tonga_islands_english_pipeline pipeline MarianTransformer from arinapav
+author: John Snow Labs
+name: helsinki_nlp_finetuned_russian_tonga_tonga_islands_english_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`helsinki_nlp_finetuned_russian_tonga_tonga_islands_english_pipeline` is a English model originally trained by arinapav.
+
+{:.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/helsinki_nlp_finetuned_russian_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725863446170.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/helsinki_nlp_finetuned_russian_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725863446170.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
+
+pipeline = PretrainedPipeline("helsinki_nlp_finetuned_russian_tonga_tonga_islands_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("helsinki_nlp_finetuned_russian_tonga_tonga_islands_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|helsinki_nlp_finetuned_russian_tonga_tonga_islands_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|526.9 MB|
+
+## References
+
+https://huggingface.co/arinapav/Helsinki-NLP-finetuned-ru-to-en
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-hensinki_english_spanish_finetuned_spanish_tonga_tonga_islands_english_tateoba_en.md b/docs/_posts/ahmedlone127/2024-09-09-hensinki_english_spanish_finetuned_spanish_tonga_tonga_islands_english_tateoba_en.md
new file mode 100644
index 00000000000000..12b8561758624f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-hensinki_english_spanish_finetuned_spanish_tonga_tonga_islands_english_tateoba_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English hensinki_english_spanish_finetuned_spanish_tonga_tonga_islands_english_tateoba MarianTransformer from beanslmao
+author: John Snow Labs
+name: hensinki_english_spanish_finetuned_spanish_tonga_tonga_islands_english_tateoba
+date: 2024-09-09
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hensinki_english_spanish_finetuned_spanish_tonga_tonga_islands_english_tateoba` is a English model originally trained by beanslmao.
+
+{:.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/hensinki_english_spanish_finetuned_spanish_tonga_tonga_islands_english_tateoba_en_5.5.0_3.0_1725840114151.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hensinki_english_spanish_finetuned_spanish_tonga_tonga_islands_english_tateoba_en_5.5.0_3.0_1725840114151.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("hensinki_english_spanish_finetuned_spanish_tonga_tonga_islands_english_tateoba","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("hensinki_english_spanish_finetuned_spanish_tonga_tonga_islands_english_tateoba","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hensinki_english_spanish_finetuned_spanish_tonga_tonga_islands_english_tateoba|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|539.7 MB|
+
+## References
+
+https://huggingface.co/beanslmao/hensinki-en-es-finetuned-spanish-to-english-tateoba
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-hensinki_spanish_english_finetuned_spanish_tonga_tonga_islands_english_tateoba_en.md b/docs/_posts/ahmedlone127/2024-09-09-hensinki_spanish_english_finetuned_spanish_tonga_tonga_islands_english_tateoba_en.md
new file mode 100644
index 00000000000000..24929bc4a2e82b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-hensinki_spanish_english_finetuned_spanish_tonga_tonga_islands_english_tateoba_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English hensinki_spanish_english_finetuned_spanish_tonga_tonga_islands_english_tateoba MarianTransformer from beanslmao
+author: John Snow Labs
+name: hensinki_spanish_english_finetuned_spanish_tonga_tonga_islands_english_tateoba
+date: 2024-09-09
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hensinki_spanish_english_finetuned_spanish_tonga_tonga_islands_english_tateoba` is a English model originally trained by beanslmao.
+
+{:.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/hensinki_spanish_english_finetuned_spanish_tonga_tonga_islands_english_tateoba_en_5.5.0_3.0_1725840028230.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hensinki_spanish_english_finetuned_spanish_tonga_tonga_islands_english_tateoba_en_5.5.0_3.0_1725840028230.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("hensinki_spanish_english_finetuned_spanish_tonga_tonga_islands_english_tateoba","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("hensinki_spanish_english_finetuned_spanish_tonga_tonga_islands_english_tateoba","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hensinki_spanish_english_finetuned_spanish_tonga_tonga_islands_english_tateoba|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|539.3 MB|
+
+## References
+
+https://huggingface.co/beanslmao/hensinki-es-en-finetuned-spanish-to-english-tateoba
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-hensinki_spanish_english_finetuned_spanish_tonga_tonga_islands_english_tateoba_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-hensinki_spanish_english_finetuned_spanish_tonga_tonga_islands_english_tateoba_pipeline_en.md
new file mode 100644
index 00000000000000..563dfbb28df961
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-hensinki_spanish_english_finetuned_spanish_tonga_tonga_islands_english_tateoba_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English hensinki_spanish_english_finetuned_spanish_tonga_tonga_islands_english_tateoba_pipeline pipeline MarianTransformer from beanslmao
+author: John Snow Labs
+name: hensinki_spanish_english_finetuned_spanish_tonga_tonga_islands_english_tateoba_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hensinki_spanish_english_finetuned_spanish_tonga_tonga_islands_english_tateoba_pipeline` is a English model originally trained by beanslmao.
+
+{:.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/hensinki_spanish_english_finetuned_spanish_tonga_tonga_islands_english_tateoba_pipeline_en_5.5.0_3.0_1725840056677.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hensinki_spanish_english_finetuned_spanish_tonga_tonga_islands_english_tateoba_pipeline_en_5.5.0_3.0_1725840056677.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
+
+pipeline = PretrainedPipeline("hensinki_spanish_english_finetuned_spanish_tonga_tonga_islands_english_tateoba_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hensinki_spanish_english_finetuned_spanish_tonga_tonga_islands_english_tateoba_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hensinki_spanish_english_finetuned_spanish_tonga_tonga_islands_english_tateoba_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|539.8 MB|
+
+## References
+
+https://huggingface.co/beanslmao/hensinki-es-en-finetuned-spanish-to-english-tateoba
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-hesroberta_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-hesroberta_pipeline_en.md
new file mode 100644
index 00000000000000..13e41597c196fd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-hesroberta_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English hesroberta_pipeline pipeline RoBertaEmbeddings from Chettaniiay
+author: John Snow Labs
+name: hesroberta_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hesroberta_pipeline` is a English model originally trained by Chettaniiay.
+
+{:.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/hesroberta_pipeline_en_5.5.0_3.0_1725883229741.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hesroberta_pipeline_en_5.5.0_3.0_1725883229741.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
+
+pipeline = PretrainedPipeline("hesroberta_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("hesroberta_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hesroberta_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.4 MB|
+
+## References
+
+https://huggingface.co/Chettaniiay/HESRoberTA
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-hihi_en.md b/docs/_posts/ahmedlone127/2024-09-09-hihi_en.md
new file mode 100644
index 00000000000000..a27290dfe3ece7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-hihi_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English hihi MarianTransformer from khoango18
+author: John Snow Labs
+name: hihi
+date: 2024-09-09
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hihi` is a English model originally trained by khoango18.
+
+{:.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/hihi_en_5.5.0_3.0_1725864873183.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hihi_en_5.5.0_3.0_1725864873183.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("hihi","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("hihi","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|hihi|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|540.1 MB|
+
+## References
+
+https://huggingface.co/khoango18/hihi
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-iwslt17_marian_small_ctx4_cwd2_english_french_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-iwslt17_marian_small_ctx4_cwd2_english_french_pipeline_en.md
new file mode 100644
index 00000000000000..307897a282d847
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-iwslt17_marian_small_ctx4_cwd2_english_french_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English iwslt17_marian_small_ctx4_cwd2_english_french_pipeline pipeline MarianTransformer from context-mt
+author: John Snow Labs
+name: iwslt17_marian_small_ctx4_cwd2_english_french_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`iwslt17_marian_small_ctx4_cwd2_english_french_pipeline` is a English model originally trained by context-mt.
+
+{:.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/iwslt17_marian_small_ctx4_cwd2_english_french_pipeline_en_5.5.0_3.0_1725863260843.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/iwslt17_marian_small_ctx4_cwd2_english_french_pipeline_en_5.5.0_3.0_1725863260843.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
+
+pipeline = PretrainedPipeline("iwslt17_marian_small_ctx4_cwd2_english_french_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("iwslt17_marian_small_ctx4_cwd2_english_french_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|iwslt17_marian_small_ctx4_cwd2_english_french_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|509.0 MB|
+
+## References
+
+https://huggingface.co/context-mt/iwslt17-marian-small-ctx4-cwd2-en-fr
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-job_listing_relevance_model_en.md b/docs/_posts/ahmedlone127/2024-09-09-job_listing_relevance_model_en.md
new file mode 100644
index 00000000000000..6f64a8325351b6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-job_listing_relevance_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English job_listing_relevance_model XlmRoBertaForSequenceClassification from saattrupdan
+author: John Snow Labs
+name: job_listing_relevance_model
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`job_listing_relevance_model` is a English model originally trained by saattrupdan.
+
+{:.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/job_listing_relevance_model_en_5.5.0_3.0_1725871458431.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/job_listing_relevance_model_en_5.5.0_3.0_1725871458431.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("job_listing_relevance_model","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("job_listing_relevance_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|job_listing_relevance_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|774.9 MB|
+
+## References
+
+https://huggingface.co/saattrupdan/job-listing-relevance-model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-kaz_roberta_base_ft_qa_english_maltese_tonga_tonga_islands_kaz_kk.md b/docs/_posts/ahmedlone127/2024-09-09-kaz_roberta_base_ft_qa_english_maltese_tonga_tonga_islands_kaz_kk.md
new file mode 100644
index 00000000000000..7f91934b4d2860
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-kaz_roberta_base_ft_qa_english_maltese_tonga_tonga_islands_kaz_kk.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: Kazakh kaz_roberta_base_ft_qa_english_maltese_tonga_tonga_islands_kaz RoBertaForQuestionAnswering from med-alex
+author: John Snow Labs
+name: kaz_roberta_base_ft_qa_english_maltese_tonga_tonga_islands_kaz
+date: 2024-09-09
+tags: [kk, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: kk
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kaz_roberta_base_ft_qa_english_maltese_tonga_tonga_islands_kaz` is a Kazakh model originally trained by med-alex.
+
+{:.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/kaz_roberta_base_ft_qa_english_maltese_tonga_tonga_islands_kaz_kk_5.5.0_3.0_1725875764430.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kaz_roberta_base_ft_qa_english_maltese_tonga_tonga_islands_kaz_kk_5.5.0_3.0_1725875764430.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("kaz_roberta_base_ft_qa_english_maltese_tonga_tonga_islands_kaz","kk") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("kaz_roberta_base_ft_qa_english_maltese_tonga_tonga_islands_kaz", "kk")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kaz_roberta_base_ft_qa_english_maltese_tonga_tonga_islands_kaz|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|kk|
+|Size:|311.7 MB|
+
+## References
+
+https://huggingface.co/med-alex/kaz-roberta-base-ft-qa-en-mt-to-kaz
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-kaz_roberta_base_ft_qa_english_maltese_tonga_tonga_islands_kaz_pipeline_kk.md b/docs/_posts/ahmedlone127/2024-09-09-kaz_roberta_base_ft_qa_english_maltese_tonga_tonga_islands_kaz_pipeline_kk.md
new file mode 100644
index 00000000000000..6317b1eca51dad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-kaz_roberta_base_ft_qa_english_maltese_tonga_tonga_islands_kaz_pipeline_kk.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Kazakh kaz_roberta_base_ft_qa_english_maltese_tonga_tonga_islands_kaz_pipeline pipeline RoBertaForQuestionAnswering from med-alex
+author: John Snow Labs
+name: kaz_roberta_base_ft_qa_english_maltese_tonga_tonga_islands_kaz_pipeline
+date: 2024-09-09
+tags: [kk, open_source, pipeline, onnx]
+task: Question Answering
+language: kk
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kaz_roberta_base_ft_qa_english_maltese_tonga_tonga_islands_kaz_pipeline` is a Kazakh model originally trained by med-alex.
+
+{:.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/kaz_roberta_base_ft_qa_english_maltese_tonga_tonga_islands_kaz_pipeline_kk_5.5.0_3.0_1725875778898.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kaz_roberta_base_ft_qa_english_maltese_tonga_tonga_islands_kaz_pipeline_kk_5.5.0_3.0_1725875778898.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
+
+pipeline = PretrainedPipeline("kaz_roberta_base_ft_qa_english_maltese_tonga_tonga_islands_kaz_pipeline", lang = "kk")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("kaz_roberta_base_ft_qa_english_maltese_tonga_tonga_islands_kaz_pipeline", lang = "kk")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kaz_roberta_base_ft_qa_english_maltese_tonga_tonga_islands_kaz_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|kk|
+|Size:|311.7 MB|
+
+## References
+
+https://huggingface.co/med-alex/kaz-roberta-base-ft-qa-en-mt-to-kaz
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-kcbert_sentiment_v2_01_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-kcbert_sentiment_v2_01_pipeline_en.md
new file mode 100644
index 00000000000000..93eea815f92c10
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-kcbert_sentiment_v2_01_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English kcbert_sentiment_v2_01_pipeline pipeline BertForSequenceClassification from ilmin
+author: John Snow Labs
+name: kcbert_sentiment_v2_01_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kcbert_sentiment_v2_01_pipeline` is a English model originally trained by ilmin.
+
+{:.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/kcbert_sentiment_v2_01_pipeline_en_5.5.0_3.0_1725856250784.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kcbert_sentiment_v2_01_pipeline_en_5.5.0_3.0_1725856250784.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
+
+pipeline = PretrainedPipeline("kcbert_sentiment_v2_01_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("kcbert_sentiment_v2_01_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|kcbert_sentiment_v2_01_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|408.5 MB|
+
+## References
+
+https://huggingface.co/ilmin/KcBERT_sentiment_v2.01
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-koelectra_small_v2_distilled_korquad_384_en.md b/docs/_posts/ahmedlone127/2024-09-09-koelectra_small_v2_distilled_korquad_384_en.md
new file mode 100644
index 00000000000000..c03424df2f31a0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-koelectra_small_v2_distilled_korquad_384_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English koelectra_small_v2_distilled_korquad_384 RoBertaForQuestionAnswering from Mary8
+author: John Snow Labs
+name: koelectra_small_v2_distilled_korquad_384
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`koelectra_small_v2_distilled_korquad_384` is a English model originally trained by Mary8.
+
+{:.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/koelectra_small_v2_distilled_korquad_384_en_5.5.0_3.0_1725867358106.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/koelectra_small_v2_distilled_korquad_384_en_5.5.0_3.0_1725867358106.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("koelectra_small_v2_distilled_korquad_384","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("koelectra_small_v2_distilled_korquad_384", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|koelectra_small_v2_distilled_korquad_384|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|306.9 MB|
+
+## References
+
+https://huggingface.co/Mary8/koelectra-small-v2-distilled-korquad-384
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-lab1_finetuning_max129_en.md b/docs/_posts/ahmedlone127/2024-09-09-lab1_finetuning_max129_en.md
new file mode 100644
index 00000000000000..b5edddb0a29b92
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-lab1_finetuning_max129_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English lab1_finetuning_max129 MarianTransformer from max129
+author: John Snow Labs
+name: lab1_finetuning_max129
+date: 2024-09-09
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lab1_finetuning_max129` is a English model originally trained by max129.
+
+{:.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/lab1_finetuning_max129_en_5.5.0_3.0_1725840012110.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lab1_finetuning_max129_en_5.5.0_3.0_1725840012110.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("lab1_finetuning_max129","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("lab1_finetuning_max129","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lab1_finetuning_max129|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.1 MB|
+
+## References
+
+https://huggingface.co/max129/lab1_finetuning
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-lab1_finetuning_max129_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-lab1_finetuning_max129_pipeline_en.md
new file mode 100644
index 00000000000000..74c92388eb79cc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-lab1_finetuning_max129_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English lab1_finetuning_max129_pipeline pipeline MarianTransformer from max129
+author: John Snow Labs
+name: lab1_finetuning_max129_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lab1_finetuning_max129_pipeline` is a English model originally trained by max129.
+
+{:.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/lab1_finetuning_max129_pipeline_en_5.5.0_3.0_1725840037536.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lab1_finetuning_max129_pipeline_en_5.5.0_3.0_1725840037536.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
+
+pipeline = PretrainedPipeline("lab1_finetuning_max129_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lab1_finetuning_max129_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lab1_finetuning_max129_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|508.6 MB|
+
+## References
+
+https://huggingface.co/max129/lab1_finetuning
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-lab1_random_tchoudh8_en.md b/docs/_posts/ahmedlone127/2024-09-09-lab1_random_tchoudh8_en.md
new file mode 100644
index 00000000000000..dbb90f60ec75ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-lab1_random_tchoudh8_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English lab1_random_tchoudh8 MarianTransformer from tchoudh8
+author: John Snow Labs
+name: lab1_random_tchoudh8
+date: 2024-09-09
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lab1_random_tchoudh8` is a English model originally trained by tchoudh8.
+
+{:.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/lab1_random_tchoudh8_en_5.5.0_3.0_1725840569963.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lab1_random_tchoudh8_en_5.5.0_3.0_1725840569963.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("lab1_random_tchoudh8","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("lab1_random_tchoudh8","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lab1_random_tchoudh8|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|510.2 MB|
+
+## References
+
+https://huggingface.co/tchoudh8/lab1_random
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-lab1_random_tchoudh8_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-lab1_random_tchoudh8_pipeline_en.md
new file mode 100644
index 00000000000000..e58115bc5d816c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-lab1_random_tchoudh8_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English lab1_random_tchoudh8_pipeline pipeline MarianTransformer from tchoudh8
+author: John Snow Labs
+name: lab1_random_tchoudh8_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lab1_random_tchoudh8_pipeline` is a English model originally trained by tchoudh8.
+
+{:.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/lab1_random_tchoudh8_pipeline_en_5.5.0_3.0_1725840594507.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lab1_random_tchoudh8_pipeline_en_5.5.0_3.0_1725840594507.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
+
+pipeline = PretrainedPipeline("lab1_random_tchoudh8_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lab1_random_tchoudh8_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lab1_random_tchoudh8_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|510.7 MB|
+
+## References
+
+https://huggingface.co/tchoudh8/lab1_random
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-lab1_random_truly_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-lab1_random_truly_pipeline_en.md
new file mode 100644
index 00000000000000..82640cdcbf8c1f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-lab1_random_truly_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English lab1_random_truly_pipeline pipeline MarianTransformer from Viennes
+author: John Snow Labs
+name: lab1_random_truly_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lab1_random_truly_pipeline` is a English model originally trained by Viennes.
+
+{:.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/lab1_random_truly_pipeline_en_5.5.0_3.0_1725840345926.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lab1_random_truly_pipeline_en_5.5.0_3.0_1725840345926.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
+
+pipeline = PretrainedPipeline("lab1_random_truly_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("lab1_random_truly_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lab1_random_truly_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|508.8 MB|
+
+## References
+
+https://huggingface.co/Viennes/lab1_random_truly
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-lab2_adam_reshphil_en.md b/docs/_posts/ahmedlone127/2024-09-09-lab2_adam_reshphil_en.md
new file mode 100644
index 00000000000000..c93e0b5d5a30aa
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-lab2_adam_reshphil_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English lab2_adam_reshphil MarianTransformer from Reshphil
+author: John Snow Labs
+name: lab2_adam_reshphil
+date: 2024-09-09
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lab2_adam_reshphil` is a English model originally trained by Reshphil.
+
+{:.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/lab2_adam_reshphil_en_5.5.0_3.0_1725840832282.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lab2_adam_reshphil_en_5.5.0_3.0_1725840832282.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("lab2_adam_reshphil","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("lab2_adam_reshphil","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|lab2_adam_reshphil|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.3 MB|
+
+## References
+
+https://huggingface.co/Reshphil/lab2_adam
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-legistorm_categorizer_seqclass_deberta_v1_en.md b/docs/_posts/ahmedlone127/2024-09-09-legistorm_categorizer_seqclass_deberta_v1_en.md
new file mode 100644
index 00000000000000..30d9ff142fefb6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-legistorm_categorizer_seqclass_deberta_v1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English legistorm_categorizer_seqclass_deberta_v1 DeBertaForSequenceClassification from leobg
+author: John Snow Labs
+name: legistorm_categorizer_seqclass_deberta_v1
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legistorm_categorizer_seqclass_deberta_v1` is a English model originally trained by leobg.
+
+{:.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/legistorm_categorizer_seqclass_deberta_v1_en_5.5.0_3.0_1725850233088.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legistorm_categorizer_seqclass_deberta_v1_en_5.5.0_3.0_1725850233088.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("legistorm_categorizer_seqclass_deberta_v1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("legistorm_categorizer_seqclass_deberta_v1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|legistorm_categorizer_seqclass_deberta_v1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|427.1 MB|
+
+## References
+
+https://huggingface.co/leobg/legistorm-categorizer-seqclass-deberta-v1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-legistorm_categorizer_seqclass_deberta_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-legistorm_categorizer_seqclass_deberta_v1_pipeline_en.md
new file mode 100644
index 00000000000000..2f08cc436e1f5f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-legistorm_categorizer_seqclass_deberta_v1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English legistorm_categorizer_seqclass_deberta_v1_pipeline pipeline DeBertaForSequenceClassification from leobg
+author: John Snow Labs
+name: legistorm_categorizer_seqclass_deberta_v1_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legistorm_categorizer_seqclass_deberta_v1_pipeline` is a English model originally trained by leobg.
+
+{:.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/legistorm_categorizer_seqclass_deberta_v1_pipeline_en_5.5.0_3.0_1725850283600.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legistorm_categorizer_seqclass_deberta_v1_pipeline_en_5.5.0_3.0_1725850283600.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
+
+pipeline = PretrainedPipeline("legistorm_categorizer_seqclass_deberta_v1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("legistorm_categorizer_seqclass_deberta_v1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|legistorm_categorizer_seqclass_deberta_v1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|427.1 MB|
+
+## References
+
+https://huggingface.co/leobg/legistorm-categorizer-seqclass-deberta-v1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-maltese_align_finetuned_sum3_thai_tonga_tonga_islands_english_en.md b/docs/_posts/ahmedlone127/2024-09-09-maltese_align_finetuned_sum3_thai_tonga_tonga_islands_english_en.md
new file mode 100644
index 00000000000000..3c3e3928a30470
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-maltese_align_finetuned_sum3_thai_tonga_tonga_islands_english_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English maltese_align_finetuned_sum3_thai_tonga_tonga_islands_english MarianTransformer from saksornr
+author: John Snow Labs
+name: maltese_align_finetuned_sum3_thai_tonga_tonga_islands_english
+date: 2024-09-09
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`maltese_align_finetuned_sum3_thai_tonga_tonga_islands_english` is a English model originally trained by saksornr.
+
+{:.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/maltese_align_finetuned_sum3_thai_tonga_tonga_islands_english_en_5.5.0_3.0_1725840361255.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/maltese_align_finetuned_sum3_thai_tonga_tonga_islands_english_en_5.5.0_3.0_1725840361255.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("maltese_align_finetuned_sum3_thai_tonga_tonga_islands_english","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("maltese_align_finetuned_sum3_thai_tonga_tonga_islands_english","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|maltese_align_finetuned_sum3_thai_tonga_tonga_islands_english|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|530.1 MB|
+
+## References
+
+https://huggingface.co/saksornr/mt-align-finetuned-SUM3-th-to-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-maltese_align_finetuned_sum3_thai_tonga_tonga_islands_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-maltese_align_finetuned_sum3_thai_tonga_tonga_islands_english_pipeline_en.md
new file mode 100644
index 00000000000000..cf26575d04037c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-maltese_align_finetuned_sum3_thai_tonga_tonga_islands_english_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English maltese_align_finetuned_sum3_thai_tonga_tonga_islands_english_pipeline pipeline MarianTransformer from saksornr
+author: John Snow Labs
+name: maltese_align_finetuned_sum3_thai_tonga_tonga_islands_english_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`maltese_align_finetuned_sum3_thai_tonga_tonga_islands_english_pipeline` is a English model originally trained by saksornr.
+
+{:.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/maltese_align_finetuned_sum3_thai_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725840387635.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/maltese_align_finetuned_sum3_thai_tonga_tonga_islands_english_pipeline_en_5.5.0_3.0_1725840387635.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
+
+pipeline = PretrainedPipeline("maltese_align_finetuned_sum3_thai_tonga_tonga_islands_english_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("maltese_align_finetuned_sum3_thai_tonga_tonga_islands_english_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|maltese_align_finetuned_sum3_thai_tonga_tonga_islands_english_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|530.7 MB|
+
+## References
+
+https://huggingface.co/saksornr/mt-align-finetuned-SUM3-th-to-en
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-maltese_coref_english_hebrew_modern_gender_en.md b/docs/_posts/ahmedlone127/2024-09-09-maltese_coref_english_hebrew_modern_gender_en.md
new file mode 100644
index 00000000000000..ace97220134490
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-maltese_coref_english_hebrew_modern_gender_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English maltese_coref_english_hebrew_modern_gender MarianTransformer from nlphuji
+author: John Snow Labs
+name: maltese_coref_english_hebrew_modern_gender
+date: 2024-09-09
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`maltese_coref_english_hebrew_modern_gender` is a English model originally trained by nlphuji.
+
+{:.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/maltese_coref_english_hebrew_modern_gender_en_5.5.0_3.0_1725863244586.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/maltese_coref_english_hebrew_modern_gender_en_5.5.0_3.0_1725863244586.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("maltese_coref_english_hebrew_modern_gender","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("maltese_coref_english_hebrew_modern_gender","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|maltese_coref_english_hebrew_modern_gender|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|545.2 MB|
+
+## References
+
+https://huggingface.co/nlphuji/mt_coref_en_he_gender
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-marathi_marh_val_h_mr.md b/docs/_posts/ahmedlone127/2024-09-09-marathi_marh_val_h_mr.md
new file mode 100644
index 00000000000000..302c403356398b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-marathi_marh_val_h_mr.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Marathi marathi_marh_val_h WhisperForCTC from simran14
+author: John Snow Labs
+name: marathi_marh_val_h
+date: 2024-09-09
+tags: [mr, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: mr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marathi_marh_val_h` is a Marathi model originally trained by simran14.
+
+{:.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/marathi_marh_val_h_mr_5.5.0_3.0_1725841793999.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marathi_marh_val_h_mr_5.5.0_3.0_1725841793999.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
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("marathi_marh_val_h","mr") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("marathi_marh_val_h", "mr")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marathi_marh_val_h|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|mr|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/simran14/mr-val-h
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_sebastians_en.md b/docs/_posts/ahmedlone127/2024-09-09-marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_sebastians_en.md
new file mode 100644
index 00000000000000..4012a84ad4b7c9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_sebastians_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_sebastians MarianTransformer from SebastianS
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_sebastians
+date: 2024-09-09
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_sebastians` is a English model originally trained by SebastianS.
+
+{:.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/marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_sebastians_en_5.5.0_3.0_1725840205728.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_sebastians_en_5.5.0_3.0_1725840205728.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_sebastians","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_sebastians","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_sebastians|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.3 MB|
+
+## References
+
+https://huggingface.co/SebastianS/marian-finetuned-kde4-en-to-fr-accelerate
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_sebastians_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_sebastians_pipeline_en.md
new file mode 100644
index 00000000000000..2270c8a67d47d1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_sebastians_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_sebastians_pipeline pipeline MarianTransformer from SebastianS
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_sebastians_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_sebastians_pipeline` is a English model originally trained by SebastianS.
+
+{:.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/marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_sebastians_pipeline_en_5.5.0_3.0_1725840231239.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_sebastians_pipeline_en_5.5.0_3.0_1725840231239.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
+
+pipeline = PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_sebastians_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_sebastians_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_accelerate_sebastians_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|508.8 MB|
+
+## References
+
+https://huggingface.co/SebastianS/marian-finetuned-kde4-en-to-fr-accelerate
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-marian_finetuned_kde4_english_tonga_tonga_islands_french_al_fa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-marian_finetuned_kde4_english_tonga_tonga_islands_french_al_fa_pipeline_en.md
new file mode 100644
index 00000000000000..fe262027af924e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-marian_finetuned_kde4_english_tonga_tonga_islands_french_al_fa_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_al_fa_pipeline pipeline MarianTransformer from al-fa
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_al_fa_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_al_fa_pipeline` is a English model originally trained by al-fa.
+
+{:.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/marian_finetuned_kde4_english_tonga_tonga_islands_french_al_fa_pipeline_en_5.5.0_3.0_1725864991270.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_al_fa_pipeline_en_5.5.0_3.0_1725864991270.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
+
+pipeline = PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_al_fa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_al_fa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_al_fa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|508.6 MB|
+
+## References
+
+https://huggingface.co/al-fa/marian-finetuned-kde4-en-to-fr
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-marian_finetuned_kde4_english_tonga_tonga_islands_french_aroot_en.md b/docs/_posts/ahmedlone127/2024-09-09-marian_finetuned_kde4_english_tonga_tonga_islands_french_aroot_en.md
new file mode 100644
index 00000000000000..b31202735e3774
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-marian_finetuned_kde4_english_tonga_tonga_islands_french_aroot_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_aroot MarianTransformer from aroot
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_aroot
+date: 2024-09-09
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_aroot` is a English model originally trained by aroot.
+
+{:.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/marian_finetuned_kde4_english_tonga_tonga_islands_french_aroot_en_5.5.0_3.0_1725840779867.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_aroot_en_5.5.0_3.0_1725840779867.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_aroot","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_aroot","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_aroot|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.2 MB|
+
+## References
+
+https://huggingface.co/aroot/marian-finetuned-kde4-en-to-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-marian_finetuned_kde4_english_tonga_tonga_islands_french_hypurci_en.md b/docs/_posts/ahmedlone127/2024-09-09-marian_finetuned_kde4_english_tonga_tonga_islands_french_hypurci_en.md
new file mode 100644
index 00000000000000..18a8961bcbab8e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-marian_finetuned_kde4_english_tonga_tonga_islands_french_hypurci_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_hypurci MarianTransformer from Hypurci
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_hypurci
+date: 2024-09-09
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_hypurci` is a English model originally trained by Hypurci.
+
+{:.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/marian_finetuned_kde4_english_tonga_tonga_islands_french_hypurci_en_5.5.0_3.0_1725840446524.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_hypurci_en_5.5.0_3.0_1725840446524.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_hypurci","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_hypurci","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_hypurci|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.1 MB|
+
+## References
+
+https://huggingface.co/Hypurci/marian-finetuned-kde4-en-to-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-marian_finetuned_kde4_english_tonga_tonga_islands_french_ksumarshmallow_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-marian_finetuned_kde4_english_tonga_tonga_islands_french_ksumarshmallow_pipeline_en.md
new file mode 100644
index 00000000000000..2c9e733f996adb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-marian_finetuned_kde4_english_tonga_tonga_islands_french_ksumarshmallow_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_ksumarshmallow_pipeline pipeline MarianTransformer from ksumarshmallow
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_ksumarshmallow_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_ksumarshmallow_pipeline` is a English model originally trained by ksumarshmallow.
+
+{:.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/marian_finetuned_kde4_english_tonga_tonga_islands_french_ksumarshmallow_pipeline_en_5.5.0_3.0_1725840757830.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_ksumarshmallow_pipeline_en_5.5.0_3.0_1725840757830.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
+
+pipeline = PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_ksumarshmallow_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_ksumarshmallow_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_ksumarshmallow_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|508.7 MB|
+
+## References
+
+https://huggingface.co/ksumarshmallow/marian-finetuned-kde4-en-to-fr
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-marian_finetuned_kde4_english_tonga_tonga_islands_french_lyk0013_en.md b/docs/_posts/ahmedlone127/2024-09-09-marian_finetuned_kde4_english_tonga_tonga_islands_french_lyk0013_en.md
new file mode 100644
index 00000000000000..99c10399752e48
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-marian_finetuned_kde4_english_tonga_tonga_islands_french_lyk0013_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_lyk0013 MarianTransformer from lyk0013
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_lyk0013
+date: 2024-09-09
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_lyk0013` is a English model originally trained by lyk0013.
+
+{:.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/marian_finetuned_kde4_english_tonga_tonga_islands_french_lyk0013_en_5.5.0_3.0_1725863063420.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_lyk0013_en_5.5.0_3.0_1725863063420.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_lyk0013","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("marian_finetuned_kde4_english_tonga_tonga_islands_french_lyk0013","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_lyk0013|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.4 MB|
+
+## References
+
+https://huggingface.co/lyk0013/marian-finetuned-kde4-en-to-fr
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-marian_finetuned_kde4_english_tonga_tonga_islands_french_lyk0013_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-marian_finetuned_kde4_english_tonga_tonga_islands_french_lyk0013_pipeline_en.md
new file mode 100644
index 00000000000000..d5ea8584e84d86
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-marian_finetuned_kde4_english_tonga_tonga_islands_french_lyk0013_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English marian_finetuned_kde4_english_tonga_tonga_islands_french_lyk0013_pipeline pipeline MarianTransformer from lyk0013
+author: John Snow Labs
+name: marian_finetuned_kde4_english_tonga_tonga_islands_french_lyk0013_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_finetuned_kde4_english_tonga_tonga_islands_french_lyk0013_pipeline` is a English model originally trained by lyk0013.
+
+{:.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/marian_finetuned_kde4_english_tonga_tonga_islands_french_lyk0013_pipeline_en_5.5.0_3.0_1725863091138.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_finetuned_kde4_english_tonga_tonga_islands_french_lyk0013_pipeline_en_5.5.0_3.0_1725863091138.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
+
+pipeline = PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_lyk0013_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("marian_finetuned_kde4_english_tonga_tonga_islands_french_lyk0013_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_finetuned_kde4_english_tonga_tonga_islands_french_lyk0013_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|509.0 MB|
+
+## References
+
+https://huggingface.co/lyk0013/marian-finetuned-kde4-en-to-fr
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-marian_formality_fine_tuned_english_german_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-marian_formality_fine_tuned_english_german_pipeline_en.md
new file mode 100644
index 00000000000000..43e28eec5b6a5a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-marian_formality_fine_tuned_english_german_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English marian_formality_fine_tuned_english_german_pipeline pipeline MarianTransformer from laniqo
+author: John Snow Labs
+name: marian_formality_fine_tuned_english_german_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marian_formality_fine_tuned_english_german_pipeline` is a English model originally trained by laniqo.
+
+{:.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/marian_formality_fine_tuned_english_german_pipeline_en_5.5.0_3.0_1725866253283.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marian_formality_fine_tuned_english_german_pipeline_en_5.5.0_3.0_1725866253283.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
+
+pipeline = PretrainedPipeline("marian_formality_fine_tuned_english_german_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("marian_formality_fine_tuned_english_german_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|marian_formality_fine_tuned_english_german_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|900.7 MB|
+
+## References
+
+https://huggingface.co/laniqo/marian_formality_fine_tuned_en_de
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-mdeberta_v3_base_azsci_topics_pipeline_az.md b/docs/_posts/ahmedlone127/2024-09-09-mdeberta_v3_base_azsci_topics_pipeline_az.md
new file mode 100644
index 00000000000000..034e8eb29c0849
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-mdeberta_v3_base_azsci_topics_pipeline_az.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Azerbaijani mdeberta_v3_base_azsci_topics_pipeline pipeline DeBertaForSequenceClassification from hajili
+author: John Snow Labs
+name: mdeberta_v3_base_azsci_topics_pipeline
+date: 2024-09-09
+tags: [az, open_source, pipeline, onnx]
+task: Text Classification
+language: az
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_azsci_topics_pipeline` is a Azerbaijani model originally trained by hajili.
+
+{:.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/mdeberta_v3_base_azsci_topics_pipeline_az_5.5.0_3.0_1725849639799.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_azsci_topics_pipeline_az_5.5.0_3.0_1725849639799.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
+
+pipeline = PretrainedPipeline("mdeberta_v3_base_azsci_topics_pipeline", lang = "az")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_v3_base_azsci_topics_pipeline", lang = "az")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_azsci_topics_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|az|
+|Size:|816.5 MB|
+
+## References
+
+https://huggingface.co/hajili/mdeberta-v3-base-azsci-topics
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-mdeberta_v3_base_claim_detection_en.md b/docs/_posts/ahmedlone127/2024-09-09-mdeberta_v3_base_claim_detection_en.md
new file mode 100644
index 00000000000000..ab36258eaf35dd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-mdeberta_v3_base_claim_detection_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mdeberta_v3_base_claim_detection DeBertaForSequenceClassification from Nithiwat
+author: John Snow Labs
+name: mdeberta_v3_base_claim_detection
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_claim_detection` is a English model originally trained by Nithiwat.
+
+{:.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/mdeberta_v3_base_claim_detection_en_5.5.0_3.0_1725849242077.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_claim_detection_en_5.5.0_3.0_1725849242077.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_claim_detection","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_claim_detection", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_claim_detection|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|852.1 MB|
+
+## References
+
+https://huggingface.co/Nithiwat/mdeberta-v3-base_claim-detection
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-mdeberta_v3_base_claim_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-mdeberta_v3_base_claim_detection_pipeline_en.md
new file mode 100644
index 00000000000000..046925f60f710d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-mdeberta_v3_base_claim_detection_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mdeberta_v3_base_claim_detection_pipeline pipeline DeBertaForSequenceClassification from Nithiwat
+author: John Snow Labs
+name: mdeberta_v3_base_claim_detection_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_claim_detection_pipeline` is a English model originally trained by Nithiwat.
+
+{:.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/mdeberta_v3_base_claim_detection_pipeline_en_5.5.0_3.0_1725849297629.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_claim_detection_pipeline_en_5.5.0_3.0_1725849297629.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
+
+pipeline = PretrainedPipeline("mdeberta_v3_base_claim_detection_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_v3_base_claim_detection_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_claim_detection_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|852.1 MB|
+
+## References
+
+https://huggingface.co/Nithiwat/mdeberta-v3-base_claim-detection
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-mdeberta_v3_base_faquad_nli_pipeline_pt.md b/docs/_posts/ahmedlone127/2024-09-09-mdeberta_v3_base_faquad_nli_pipeline_pt.md
new file mode 100644
index 00000000000000..6ff31b0e89c327
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-mdeberta_v3_base_faquad_nli_pipeline_pt.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Portuguese mdeberta_v3_base_faquad_nli_pipeline pipeline DeBertaForSequenceClassification from ruanchaves
+author: John Snow Labs
+name: mdeberta_v3_base_faquad_nli_pipeline
+date: 2024-09-09
+tags: [pt, open_source, pipeline, onnx]
+task: Text Classification
+language: pt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_faquad_nli_pipeline` is a Portuguese model originally trained by ruanchaves.
+
+{:.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/mdeberta_v3_base_faquad_nli_pipeline_pt_5.5.0_3.0_1725879343025.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_faquad_nli_pipeline_pt_5.5.0_3.0_1725879343025.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
+
+pipeline = PretrainedPipeline("mdeberta_v3_base_faquad_nli_pipeline", lang = "pt")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_v3_base_faquad_nli_pipeline", lang = "pt")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_faquad_nli_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|pt|
+|Size:|839.1 MB|
+
+## References
+
+https://huggingface.co/ruanchaves/mdeberta-v3-base-faquad-nli
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-mdeberta_v3_base_rte_10_en.md b/docs/_posts/ahmedlone127/2024-09-09-mdeberta_v3_base_rte_10_en.md
new file mode 100644
index 00000000000000..487bf90d18436e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-mdeberta_v3_base_rte_10_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mdeberta_v3_base_rte_10 DeBertaForSequenceClassification from tmnam20
+author: John Snow Labs
+name: mdeberta_v3_base_rte_10
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_rte_10` is a English model originally trained by tmnam20.
+
+{:.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/mdeberta_v3_base_rte_10_en_5.5.0_3.0_1725879064479.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_rte_10_en_5.5.0_3.0_1725879064479.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_rte_10","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_rte_10", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_rte_10|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|790.6 MB|
+
+## References
+
+https://huggingface.co/tmnam20/mdeberta-v3-base-rte-10
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-mdeberta_v3_base_rte_10_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-mdeberta_v3_base_rte_10_pipeline_en.md
new file mode 100644
index 00000000000000..1ce533192f4688
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-mdeberta_v3_base_rte_10_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mdeberta_v3_base_rte_10_pipeline pipeline DeBertaForSequenceClassification from tmnam20
+author: John Snow Labs
+name: mdeberta_v3_base_rte_10_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_rte_10_pipeline` is a English model originally trained by tmnam20.
+
+{:.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/mdeberta_v3_base_rte_10_pipeline_en_5.5.0_3.0_1725879208211.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_rte_10_pipeline_en_5.5.0_3.0_1725879208211.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
+
+pipeline = PretrainedPipeline("mdeberta_v3_base_rte_10_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_v3_base_rte_10_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_rte_10_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|790.7 MB|
+
+## References
+
+https://huggingface.co/tmnam20/mdeberta-v3-base-rte-10
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-mdeberta_v3_base_wnli_100_en.md b/docs/_posts/ahmedlone127/2024-09-09-mdeberta_v3_base_wnli_100_en.md
new file mode 100644
index 00000000000000..008b06073faf29
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-mdeberta_v3_base_wnli_100_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mdeberta_v3_base_wnli_100 DeBertaForSequenceClassification from tmnam20
+author: John Snow Labs
+name: mdeberta_v3_base_wnli_100
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_wnli_100` is a English model originally trained by tmnam20.
+
+{:.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/mdeberta_v3_base_wnli_100_en_5.5.0_3.0_1725849856081.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_wnli_100_en_5.5.0_3.0_1725849856081.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_wnli_100","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdeberta_v3_base_wnli_100", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_wnli_100|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|779.4 MB|
+
+## References
+
+https://huggingface.co/tmnam20/mdeberta-v3-base-wnli-100
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-mdeberta_v3_base_wnli_100_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-mdeberta_v3_base_wnli_100_pipeline_en.md
new file mode 100644
index 00000000000000..1a6ed17d49c3e0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-mdeberta_v3_base_wnli_100_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mdeberta_v3_base_wnli_100_pipeline pipeline DeBertaForSequenceClassification from tmnam20
+author: John Snow Labs
+name: mdeberta_v3_base_wnli_100_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdeberta_v3_base_wnli_100_pipeline` is a English model originally trained by tmnam20.
+
+{:.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/mdeberta_v3_base_wnli_100_pipeline_en_5.5.0_3.0_1725850004485.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdeberta_v3_base_wnli_100_pipeline_en_5.5.0_3.0_1725850004485.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
+
+pipeline = PretrainedPipeline("mdeberta_v3_base_wnli_100_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdeberta_v3_base_wnli_100_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdeberta_v3_base_wnli_100_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|779.5 MB|
+
+## References
+
+https://huggingface.co/tmnam20/mdeberta-v3-base-wnli-100
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-mdebertav3_subjectivity_dutch_nl.md b/docs/_posts/ahmedlone127/2024-09-09-mdebertav3_subjectivity_dutch_nl.md
new file mode 100644
index 00000000000000..342268c70d4738
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-mdebertav3_subjectivity_dutch_nl.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Dutch, Flemish mdebertav3_subjectivity_dutch DeBertaForSequenceClassification from GroNLP
+author: John Snow Labs
+name: mdebertav3_subjectivity_dutch
+date: 2024-09-09
+tags: [nl, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: nl
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdebertav3_subjectivity_dutch` is a Dutch, Flemish model originally trained by GroNLP.
+
+{:.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/mdebertav3_subjectivity_dutch_nl_5.5.0_3.0_1725878975707.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdebertav3_subjectivity_dutch_nl_5.5.0_3.0_1725878975707.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("mdebertav3_subjectivity_dutch","nl") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mdebertav3_subjectivity_dutch", "nl")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdebertav3_subjectivity_dutch|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|nl|
+|Size:|859.5 MB|
+
+## References
+
+https://huggingface.co/GroNLP/mdebertav3-subjectivity-dutch
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-mdebertav3_subjectivity_dutch_pipeline_nl.md b/docs/_posts/ahmedlone127/2024-09-09-mdebertav3_subjectivity_dutch_pipeline_nl.md
new file mode 100644
index 00000000000000..32d1c105d8cc15
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-mdebertav3_subjectivity_dutch_pipeline_nl.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Dutch, Flemish mdebertav3_subjectivity_dutch_pipeline pipeline DeBertaForSequenceClassification from GroNLP
+author: John Snow Labs
+name: mdebertav3_subjectivity_dutch_pipeline
+date: 2024-09-09
+tags: [nl, open_source, pipeline, onnx]
+task: Text Classification
+language: nl
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mdebertav3_subjectivity_dutch_pipeline` is a Dutch, Flemish model originally trained by GroNLP.
+
+{:.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/mdebertav3_subjectivity_dutch_pipeline_nl_5.5.0_3.0_1725879027724.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mdebertav3_subjectivity_dutch_pipeline_nl_5.5.0_3.0_1725879027724.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
+
+pipeline = PretrainedPipeline("mdebertav3_subjectivity_dutch_pipeline", lang = "nl")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mdebertav3_subjectivity_dutch_pipeline", lang = "nl")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mdebertav3_subjectivity_dutch_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|nl|
+|Size:|859.5 MB|
+
+## References
+
+https://huggingface.co/GroNLP/mdebertav3-subjectivity-dutch
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-medicalquestionanswering_en.md b/docs/_posts/ahmedlone127/2024-09-09-medicalquestionanswering_en.md
new file mode 100644
index 00000000000000..d38a12c9e82dc0
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-medicalquestionanswering_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English medicalquestionanswering BertForQuestionAnswering from GonzaloValdenebro
+author: John Snow Labs
+name: medicalquestionanswering
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, bert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medicalquestionanswering` is a English model originally trained by GonzaloValdenebro.
+
+{:.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/medicalquestionanswering_en_5.5.0_3.0_1725885296128.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medicalquestionanswering_en_5.5.0_3.0_1725885296128.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = BertForQuestionAnswering.pretrained("medicalquestionanswering","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = BertForQuestionAnswering.pretrained("medicalquestionanswering", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|medicalquestionanswering|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|249.0 MB|
+
+## References
+
+https://huggingface.co/GonzaloValdenebro/MedicalQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-mnli_microsoft_deberta_v3_large_seed_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-mnli_microsoft_deberta_v3_large_seed_3_pipeline_en.md
new file mode 100644
index 00000000000000..e71efe1d3cd6fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-mnli_microsoft_deberta_v3_large_seed_3_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mnli_microsoft_deberta_v3_large_seed_3_pipeline pipeline DeBertaForSequenceClassification from utahnlp
+author: John Snow Labs
+name: mnli_microsoft_deberta_v3_large_seed_3_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mnli_microsoft_deberta_v3_large_seed_3_pipeline` is a English model originally trained by utahnlp.
+
+{:.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/mnli_microsoft_deberta_v3_large_seed_3_pipeline_en_5.5.0_3.0_1725859324462.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mnli_microsoft_deberta_v3_large_seed_3_pipeline_en_5.5.0_3.0_1725859324462.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
+
+pipeline = PretrainedPipeline("mnli_microsoft_deberta_v3_large_seed_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mnli_microsoft_deberta_v3_large_seed_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mnli_microsoft_deberta_v3_large_seed_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/utahnlp/mnli_microsoft_deberta-v3-large_seed-3
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-mpnet_base_apple_iphone_northern_sami_reviews_en.md b/docs/_posts/ahmedlone127/2024-09-09-mpnet_base_apple_iphone_northern_sami_reviews_en.md
new file mode 100644
index 00000000000000..038f24a64fe2ef
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-mpnet_base_apple_iphone_northern_sami_reviews_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mpnet_base_apple_iphone_northern_sami_reviews MPNetForSequenceClassification from DunnBC22
+author: John Snow Labs
+name: mpnet_base_apple_iphone_northern_sami_reviews
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, mpnet]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_base_apple_iphone_northern_sami_reviews` is a English model originally trained by DunnBC22.
+
+{:.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_base_apple_iphone_northern_sami_reviews_en_5.5.0_3.0_1725881301365.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_base_apple_iphone_northern_sami_reviews_en_5.5.0_3.0_1725881301365.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = MPNetForSequenceClassification.pretrained("mpnet_base_apple_iphone_northern_sami_reviews","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = MPNetForSequenceClassification.pretrained("mpnet_base_apple_iphone_northern_sami_reviews", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnet_base_apple_iphone_northern_sami_reviews|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|391.3 MB|
+
+## References
+
+https://huggingface.co/DunnBC22/mpnet-base-apple_iphone_se_reviews
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-mpnet_base_apple_iphone_northern_sami_reviews_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-mpnet_base_apple_iphone_northern_sami_reviews_pipeline_en.md
new file mode 100644
index 00000000000000..58d98c80a70061
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-mpnet_base_apple_iphone_northern_sami_reviews_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mpnet_base_apple_iphone_northern_sami_reviews_pipeline pipeline MPNetForSequenceClassification from DunnBC22
+author: John Snow Labs
+name: mpnet_base_apple_iphone_northern_sami_reviews_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_base_apple_iphone_northern_sami_reviews_pipeline` is a English model originally trained by DunnBC22.
+
+{:.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_base_apple_iphone_northern_sami_reviews_pipeline_en_5.5.0_3.0_1725881321994.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_base_apple_iphone_northern_sami_reviews_pipeline_en_5.5.0_3.0_1725881321994.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
+
+pipeline = PretrainedPipeline("mpnet_base_apple_iphone_northern_sami_reviews_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mpnet_base_apple_iphone_northern_sami_reviews_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnet_base_apple_iphone_northern_sami_reviews_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|391.3 MB|
+
+## References
+
+https://huggingface.co/DunnBC22/mpnet-base-apple_iphone_se_reviews
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- MPNetForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-mpnet_pd_books_en.md b/docs/_posts/ahmedlone127/2024-09-09-mpnet_pd_books_en.md
new file mode 100644
index 00000000000000..96d6575086c445
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-mpnet_pd_books_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mpnet_pd_books MPNetForSequenceClassification from Gaxys
+author: John Snow Labs
+name: mpnet_pd_books
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, mpnet]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_pd_books` is a English model originally trained by Gaxys.
+
+{:.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_pd_books_en_5.5.0_3.0_1725880905437.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_pd_books_en_5.5.0_3.0_1725880905437.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = MPNetForSequenceClassification.pretrained("mpnet_pd_books","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = MPNetForSequenceClassification.pretrained("mpnet_pd_books", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnet_pd_books|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|400.4 MB|
+
+## References
+
+https://huggingface.co/Gaxys/MPnet-PD_Books
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-mpnetforclassification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-mpnetforclassification_pipeline_en.md
new file mode 100644
index 00000000000000..e474af9285e49a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-mpnetforclassification_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mpnetforclassification_pipeline pipeline MPNetForSequenceClassification from poooj
+author: John Snow Labs
+name: mpnetforclassification_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnetforclassification_pipeline` is a English model originally trained by poooj.
+
+{:.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/mpnetforclassification_pipeline_en_5.5.0_3.0_1725881061813.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnetforclassification_pipeline_en_5.5.0_3.0_1725881061813.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
+
+pipeline = PretrainedPipeline("mpnetforclassification_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mpnetforclassification_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnetforclassification_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/poooj/MPNetForClassification
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- MPNetForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-mpnetv2_com_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-mpnetv2_com_pipeline_en.md
new file mode 100644
index 00000000000000..f5de606011aa8e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-mpnetv2_com_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mpnetv2_com_pipeline pipeline MPNetEmbeddings from Neokun004
+author: John Snow Labs
+name: mpnetv2_com_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnetv2_com_pipeline` is a English model originally trained by Neokun004.
+
+{:.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/mpnetv2_com_pipeline_en_5.5.0_3.0_1725874671796.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnetv2_com_pipeline_en_5.5.0_3.0_1725874671796.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
+
+pipeline = PretrainedPipeline("mpnetv2_com_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mpnetv2_com_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mpnetv2_com_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/Neokun004/mpnetv2_com
+
+## Included Models
+
+- DocumentAssembler
+- MPNetEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-mrpc_microsoft_deberta_v3_base_seed_2_en.md b/docs/_posts/ahmedlone127/2024-09-09-mrpc_microsoft_deberta_v3_base_seed_2_en.md
new file mode 100644
index 00000000000000..37f9dccfedae9b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-mrpc_microsoft_deberta_v3_base_seed_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English mrpc_microsoft_deberta_v3_base_seed_2 DeBertaForSequenceClassification from utahnlp
+author: John Snow Labs
+name: mrpc_microsoft_deberta_v3_base_seed_2
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mrpc_microsoft_deberta_v3_base_seed_2` is a English model originally trained by utahnlp.
+
+{:.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/mrpc_microsoft_deberta_v3_base_seed_2_en_5.5.0_3.0_1725849251339.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mrpc_microsoft_deberta_v3_base_seed_2_en_5.5.0_3.0_1725849251339.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("mrpc_microsoft_deberta_v3_base_seed_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("mrpc_microsoft_deberta_v3_base_seed_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mrpc_microsoft_deberta_v3_base_seed_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|573.9 MB|
+
+## References
+
+https://huggingface.co/utahnlp/mrpc_microsoft_deberta-v3-base_seed-2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-mrpc_microsoft_deberta_v3_base_seed_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-mrpc_microsoft_deberta_v3_base_seed_2_pipeline_en.md
new file mode 100644
index 00000000000000..d194a4d3a50232
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-mrpc_microsoft_deberta_v3_base_seed_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English mrpc_microsoft_deberta_v3_base_seed_2_pipeline pipeline DeBertaForSequenceClassification from utahnlp
+author: John Snow Labs
+name: mrpc_microsoft_deberta_v3_base_seed_2_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mrpc_microsoft_deberta_v3_base_seed_2_pipeline` is a English model originally trained by utahnlp.
+
+{:.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/mrpc_microsoft_deberta_v3_base_seed_2_pipeline_en_5.5.0_3.0_1725849327121.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mrpc_microsoft_deberta_v3_base_seed_2_pipeline_en_5.5.0_3.0_1725849327121.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
+
+pipeline = PretrainedPipeline("mrpc_microsoft_deberta_v3_base_seed_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mrpc_microsoft_deberta_v3_base_seed_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mrpc_microsoft_deberta_v3_base_seed_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|573.9 MB|
+
+## References
+
+https://huggingface.co/utahnlp/mrpc_microsoft_deberta-v3-base_seed-2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-msmarco_distilbert_word2vec256k_mlm_400k_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-msmarco_distilbert_word2vec256k_mlm_400k_pipeline_en.md
new file mode 100644
index 00000000000000..569cf0194fca11
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-msmarco_distilbert_word2vec256k_mlm_400k_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English msmarco_distilbert_word2vec256k_mlm_400k_pipeline pipeline DistilBertEmbeddings from vocab-transformers
+author: John Snow Labs
+name: msmarco_distilbert_word2vec256k_mlm_400k_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`msmarco_distilbert_word2vec256k_mlm_400k_pipeline` is a English model originally trained by vocab-transformers.
+
+{:.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/msmarco_distilbert_word2vec256k_mlm_400k_pipeline_en_5.5.0_3.0_1725877953083.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/msmarco_distilbert_word2vec256k_mlm_400k_pipeline_en_5.5.0_3.0_1725877953083.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
+
+pipeline = PretrainedPipeline("msmarco_distilbert_word2vec256k_mlm_400k_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("msmarco_distilbert_word2vec256k_mlm_400k_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|msmarco_distilbert_word2vec256k_mlm_400k_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|885.6 MB|
+
+## References
+
+https://huggingface.co/vocab-transformers/msmarco-distilbert-word2vec256k-MLM_400k
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DistilBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-mt5_base_finetuned_anaphora_czech_en.md b/docs/_posts/ahmedlone127/2024-09-09-mt5_base_finetuned_anaphora_czech_en.md
new file mode 100644
index 00000000000000..50fa356213e48e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-mt5_base_finetuned_anaphora_czech_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mt5_base_finetuned_anaphora_czech T5Transformer from patrixtano
+author: John Snow Labs
+name: mt5_base_finetuned_anaphora_czech
+date: 2024-09-09
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_base_finetuned_anaphora_czech` is a English model originally trained by patrixtano.
+
+{:.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/mt5_base_finetuned_anaphora_czech_en_5.5.0_3.0_1725855580359.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_base_finetuned_anaphora_czech_en_5.5.0_3.0_1725855580359.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_base_finetuned_anaphora_czech","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_base_finetuned_anaphora_czech", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_base_finetuned_anaphora_czech|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|2.3 GB|
+
+## References
+
+https://huggingface.co/patrixtano/mt5-base-finetuned-anaphora_czech
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-mt5_base_finetuned_anaphora_czech_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-mt5_base_finetuned_anaphora_czech_pipeline_en.md
new file mode 100644
index 00000000000000..31299c51b89deb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-mt5_base_finetuned_anaphora_czech_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English mt5_base_finetuned_anaphora_czech_pipeline pipeline T5Transformer from patrixtano
+author: John Snow Labs
+name: mt5_base_finetuned_anaphora_czech_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_base_finetuned_anaphora_czech_pipeline` is a English model originally trained by patrixtano.
+
+{:.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/mt5_base_finetuned_anaphora_czech_pipeline_en_5.5.0_3.0_1725855812368.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_base_finetuned_anaphora_czech_pipeline_en_5.5.0_3.0_1725855812368.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
+
+pipeline = PretrainedPipeline("mt5_base_finetuned_anaphora_czech_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("mt5_base_finetuned_anaphora_czech_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_base_finetuned_anaphora_czech_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|2.3 GB|
+
+## References
+
+https://huggingface.co/patrixtano/mt5-base-finetuned-anaphora_czech
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-mt5_small_finetuned_anaphora_czech_en.md b/docs/_posts/ahmedlone127/2024-09-09-mt5_small_finetuned_anaphora_czech_en.md
new file mode 100644
index 00000000000000..61cd20edc7ce57
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-mt5_small_finetuned_anaphora_czech_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English mt5_small_finetuned_anaphora_czech T5Transformer from patrixtano
+author: John Snow Labs
+name: mt5_small_finetuned_anaphora_czech
+date: 2024-09-09
+tags: [en, open_source, onnx, t5, question_answering, summarization, translation, text_generation]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: T5Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained T5Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mt5_small_finetuned_anaphora_czech` is a English model originally trained by patrixtano.
+
+{:.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/mt5_small_finetuned_anaphora_czech_en_5.5.0_3.0_1725855593902.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mt5_small_finetuned_anaphora_czech_en_5.5.0_3.0_1725855593902.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+
+t5  = T5Transformer.pretrained("mt5_small_finetuned_anaphora_czech","en") \
+     .setInputCols(["document"]) \
+     .setOutputCol("output")
+
+pipeline = Pipeline().setStages([documentAssembler, t5])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+
+val t5 = T5Transformer.pretrained("mt5_small_finetuned_anaphora_czech", "en")
+    .setInputCols(Array("documents")) 
+    .setOutputCol("output") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, t5))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|mt5_small_finetuned_anaphora_czech|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[output]|
+|Language:|en|
+|Size:|1.2 GB|
+
+## References
+
+https://huggingface.co/patrixtano/mt5-small-finetuned-anaphora_czech
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-name_tonga_tonga_islands_gender_en.md b/docs/_posts/ahmedlone127/2024-09-09-name_tonga_tonga_islands_gender_en.md
new file mode 100644
index 00000000000000..7fe4c1e9986b63
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-name_tonga_tonga_islands_gender_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English name_tonga_tonga_islands_gender BertForSequenceClassification from datalearningpr
+author: John Snow Labs
+name: name_tonga_tonga_islands_gender
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`name_tonga_tonga_islands_gender` is a English model originally trained by datalearningpr.
+
+{:.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/name_tonga_tonga_islands_gender_en_5.5.0_3.0_1725852696722.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/name_tonga_tonga_islands_gender_en_5.5.0_3.0_1725852696722.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("name_tonga_tonga_islands_gender","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("name_tonga_tonga_islands_gender", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|name_tonga_tonga_islands_gender|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|383.3 MB|
+
+## References
+
+https://huggingface.co/datalearningpr/name_to_gender
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-name_tonga_tonga_islands_gender_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-name_tonga_tonga_islands_gender_pipeline_en.md
new file mode 100644
index 00000000000000..50bef7d7730f1f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-name_tonga_tonga_islands_gender_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English name_tonga_tonga_islands_gender_pipeline pipeline BertForSequenceClassification from datalearningpr
+author: John Snow Labs
+name: name_tonga_tonga_islands_gender_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`name_tonga_tonga_islands_gender_pipeline` is a English model originally trained by datalearningpr.
+
+{:.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/name_tonga_tonga_islands_gender_pipeline_en_5.5.0_3.0_1725852716096.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/name_tonga_tonga_islands_gender_pipeline_en_5.5.0_3.0_1725852716096.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
+
+pipeline = PretrainedPipeline("name_tonga_tonga_islands_gender_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("name_tonga_tonga_islands_gender_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|name_tonga_tonga_islands_gender_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|383.3 MB|
+
+## References
+
+https://huggingface.co/datalearningpr/name_to_gender
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-nepal_bhasa_model_en.md b/docs/_posts/ahmedlone127/2024-09-09-nepal_bhasa_model_en.md
new file mode 100644
index 00000000000000..8b98c1d03b6bf8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-nepal_bhasa_model_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English nepal_bhasa_model BertEmbeddings from swadesh7
+author: John Snow Labs
+name: nepal_bhasa_model
+date: 2024-09-09
+tags: [bert, en, open_source, fill_mask, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings  model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nepal_bhasa_model` is a English model originally trained by swadesh7.
+
+## 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/nepal_bhasa_model_en_5.5.0_3.0_1725876294399.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nepal_bhasa_model_en_5.5.0_3.0_1725876294399.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 =BertEmbeddings.pretrained("nepal_bhasa_model","en") \
+            .setInputCols(["documents","token"]) \
+            .setOutputCol("embeddings")
+
+pipeline = Pipeline().setStages([document_assembler, embeddings])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+```
+```scala
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("embeddings")
+    
+val embeddings = BertEmbeddings 
+    .pretrained("nepal_bhasa_model", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("embeddings") 
+
+val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nepal_bhasa_model|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+References
+
+References
+
+https://huggingface.co/swadesh7/new_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-nli_mpnet_base_v2_mbti_full_en.md b/docs/_posts/ahmedlone127/2024-09-09-nli_mpnet_base_v2_mbti_full_en.md
new file mode 100644
index 00000000000000..60d7f9d784f221
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-nli_mpnet_base_v2_mbti_full_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English nli_mpnet_base_v2_mbti_full MPNetForSequenceClassification from ClaudiaRichard
+author: John Snow Labs
+name: nli_mpnet_base_v2_mbti_full
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, mpnet]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MPNetForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MPNetForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nli_mpnet_base_v2_mbti_full` is a English model originally trained by ClaudiaRichard.
+
+{:.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/nli_mpnet_base_v2_mbti_full_en_5.5.0_3.0_1725850671788.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nli_mpnet_base_v2_mbti_full_en_5.5.0_3.0_1725850671788.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = MPNetForSequenceClassification.pretrained("nli_mpnet_base_v2_mbti_full","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = MPNetForSequenceClassification.pretrained("nli_mpnet_base_v2_mbti_full", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nli_mpnet_base_v2_mbti_full|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|408.1 MB|
+
+## References
+
+https://huggingface.co/ClaudiaRichard/nli-mpnet-base-v2_mbti_full
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-nlp4web_group80_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-nlp4web_group80_pipeline_en.md
new file mode 100644
index 00000000000000..25a3a3ff20e295
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-nlp4web_group80_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English nlp4web_group80_pipeline pipeline DistilBertForQuestionAnswering from Atypical5387
+author: John Snow Labs
+name: nlp4web_group80_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp4web_group80_pipeline` is a English model originally trained by Atypical5387.
+
+{:.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/nlp4web_group80_pipeline_en_5.5.0_3.0_1725877463217.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp4web_group80_pipeline_en_5.5.0_3.0_1725877463217.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
+
+pipeline = PretrainedPipeline("nlp4web_group80_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nlp4web_group80_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nlp4web_group80_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Atypical5387/NLP4Web_Group80
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-nusax_senti_xlm_r_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-nusax_senti_xlm_r_pipeline_en.md
new file mode 100644
index 00000000000000..dd167cee159d64
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-nusax_senti_xlm_r_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English nusax_senti_xlm_r_pipeline pipeline XlmRoBertaForSequenceClassification from Cincin-nvp
+author: John Snow Labs
+name: nusax_senti_xlm_r_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nusax_senti_xlm_r_pipeline` is a English model originally trained by Cincin-nvp.
+
+{:.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/nusax_senti_xlm_r_pipeline_en_5.5.0_3.0_1725871589566.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nusax_senti_xlm_r_pipeline_en_5.5.0_3.0_1725871589566.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
+
+pipeline = PretrainedPipeline("nusax_senti_xlm_r_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("nusax_senti_xlm_r_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nusax_senti_xlm_r_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|829.2 MB|
+
+## References
+
+https://huggingface.co/Cincin-nvp/NusaX-senti_XLM-R
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-nuzhny_english_tonga_tonga_islands_ru2_en.md b/docs/_posts/ahmedlone127/2024-09-09-nuzhny_english_tonga_tonga_islands_ru2_en.md
new file mode 100644
index 00000000000000..42e8dff1bccbb4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-nuzhny_english_tonga_tonga_islands_ru2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English nuzhny_english_tonga_tonga_islands_ru2 MarianTransformer from nuzhny
+author: John Snow Labs
+name: nuzhny_english_tonga_tonga_islands_ru2
+date: 2024-09-09
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nuzhny_english_tonga_tonga_islands_ru2` is a English model originally trained by nuzhny.
+
+{:.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/nuzhny_english_tonga_tonga_islands_ru2_en_5.5.0_3.0_1725863703288.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nuzhny_english_tonga_tonga_islands_ru2_en_5.5.0_3.0_1725863703288.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("nuzhny_english_tonga_tonga_islands_ru2","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("nuzhny_english_tonga_tonga_islands_ru2","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|nuzhny_english_tonga_tonga_islands_ru2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|525.5 MB|
+
+## References
+
+https://huggingface.co/nuzhny/nuzhny-en-to-ru2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-odia_whisper_small_v3_0_or.md b/docs/_posts/ahmedlone127/2024-09-09-odia_whisper_small_v3_0_or.md
new file mode 100644
index 00000000000000..97e0ec6dea7782
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-odia_whisper_small_v3_0_or.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Oriya (macrolanguage) odia_whisper_small_v3_0 WhisperForCTC from Ranjit
+author: John Snow Labs
+name: odia_whisper_small_v3_0
+date: 2024-09-09
+tags: [or, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: or
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`odia_whisper_small_v3_0` is a Oriya (macrolanguage) model originally trained by Ranjit.
+
+{:.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/odia_whisper_small_v3_0_or_5.5.0_3.0_1725847863070.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/odia_whisper_small_v3_0_or_5.5.0_3.0_1725847863070.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
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("odia_whisper_small_v3_0","or") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("odia_whisper_small_v3_0", "or")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|odia_whisper_small_v3_0|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|or|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/Ranjit/odia_whisper_small_v3.0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-ope_bert_v1_2_en.md b/docs/_posts/ahmedlone127/2024-09-09-ope_bert_v1_2_en.md
new file mode 100644
index 00000000000000..1f4b205dcc0f2e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-ope_bert_v1_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English ope_bert_v1_2 DistilBertEmbeddings from RyotaroOKabe
+author: John Snow Labs
+name: ope_bert_v1_2
+date: 2024-09-09
+tags: [en, open_source, onnx, embeddings, distilbert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ope_bert_v1_2` is a English model originally trained by RyotaroOKabe.
+
+{:.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/ope_bert_v1_2_en_5.5.0_3.0_1725868402857.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ope_bert_v1_2_en_5.5.0_3.0_1725868402857.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = DistilBertEmbeddings.pretrained("ope_bert_v1_2","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = DistilBertEmbeddings.pretrained("ope_bert_v1_2","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ope_bert_v1_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[distilbert]|
+|Language:|en|
+|Size:|247.4 MB|
+
+## References
+
+https://huggingface.co/RyotaroOKabe/ope_bert_v1.2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-opus_english_polish_finetuning_opus_en.md b/docs/_posts/ahmedlone127/2024-09-09-opus_english_polish_finetuning_opus_en.md
new file mode 100644
index 00000000000000..f54e3da141ffcd
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-opus_english_polish_finetuning_opus_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_english_polish_finetuning_opus MarianTransformer from clui
+author: John Snow Labs
+name: opus_english_polish_finetuning_opus
+date: 2024-09-09
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_english_polish_finetuning_opus` is a English model originally trained by clui.
+
+{:.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/opus_english_polish_finetuning_opus_en_5.5.0_3.0_1725863452773.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_english_polish_finetuning_opus_en_5.5.0_3.0_1725863452773.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_english_polish_finetuning_opus","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_english_polish_finetuning_opus","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_english_polish_finetuning_opus|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|542.0 MB|
+
+## References
+
+https://huggingface.co/clui/opus-en-pl-finetuning-opus
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-opus_english_polish_finetuning_opus_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-opus_english_polish_finetuning_opus_pipeline_en.md
new file mode 100644
index 00000000000000..ad41929e4d4ffc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-opus_english_polish_finetuning_opus_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_english_polish_finetuning_opus_pipeline pipeline MarianTransformer from clui
+author: John Snow Labs
+name: opus_english_polish_finetuning_opus_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_english_polish_finetuning_opus_pipeline` is a English model originally trained by clui.
+
+{:.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/opus_english_polish_finetuning_opus_pipeline_en_5.5.0_3.0_1725863478832.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_english_polish_finetuning_opus_pipeline_en_5.5.0_3.0_1725863478832.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
+
+pipeline = PretrainedPipeline("opus_english_polish_finetuning_opus_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_english_polish_finetuning_opus_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_english_polish_finetuning_opus_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|542.6 MB|
+
+## References
+
+https://huggingface.co/clui/opus-en-pl-finetuning-opus
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_arabic_english_finetuned_npomo_english_10_epochs_en.md b/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_arabic_english_finetuned_npomo_english_10_epochs_en.md
new file mode 100644
index 00000000000000..d566e24444af6b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_arabic_english_finetuned_npomo_english_10_epochs_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_arabic_english_finetuned_npomo_english_10_epochs MarianTransformer from UnassumingOwl
+author: John Snow Labs
+name: opus_maltese_arabic_english_finetuned_npomo_english_10_epochs
+date: 2024-09-09
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_arabic_english_finetuned_npomo_english_10_epochs` is a English model originally trained by UnassumingOwl.
+
+{:.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/opus_maltese_arabic_english_finetuned_npomo_english_10_epochs_en_5.5.0_3.0_1725840487412.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_arabic_english_finetuned_npomo_english_10_epochs_en_5.5.0_3.0_1725840487412.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_arabic_english_finetuned_npomo_english_10_epochs","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_arabic_english_finetuned_npomo_english_10_epochs","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_arabic_english_finetuned_npomo_english_10_epochs|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|528.0 MB|
+
+## References
+
+https://huggingface.co/UnassumingOwl/opus-mt-ar-en-finetuned-npomo-en-10-epochs
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_arabic_english_finetuned_npomo_english_10_epochs_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_arabic_english_finetuned_npomo_english_10_epochs_pipeline_en.md
new file mode 100644
index 00000000000000..aaf60ecbc56c0f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_arabic_english_finetuned_npomo_english_10_epochs_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_arabic_english_finetuned_npomo_english_10_epochs_pipeline pipeline MarianTransformer from UnassumingOwl
+author: John Snow Labs
+name: opus_maltese_arabic_english_finetuned_npomo_english_10_epochs_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_arabic_english_finetuned_npomo_english_10_epochs_pipeline` is a English model originally trained by UnassumingOwl.
+
+{:.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/opus_maltese_arabic_english_finetuned_npomo_english_10_epochs_pipeline_en_5.5.0_3.0_1725840514176.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_arabic_english_finetuned_npomo_english_10_epochs_pipeline_en_5.5.0_3.0_1725840514176.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
+
+pipeline = PretrainedPipeline("opus_maltese_arabic_english_finetuned_npomo_english_10_epochs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_arabic_english_finetuned_npomo_english_10_epochs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_arabic_english_finetuned_npomo_english_10_epochs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|528.5 MB|
+
+## References
+
+https://huggingface.co/UnassumingOwl/opus-mt-ar-en-finetuned-npomo-en-10-epochs
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_arabic_english_finetuned_npomo_english_5_epochs_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_arabic_english_finetuned_npomo_english_5_epochs_pipeline_en.md
new file mode 100644
index 00000000000000..b0245c30c27d69
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_arabic_english_finetuned_npomo_english_5_epochs_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_arabic_english_finetuned_npomo_english_5_epochs_pipeline pipeline MarianTransformer from UnassumingOwl
+author: John Snow Labs
+name: opus_maltese_arabic_english_finetuned_npomo_english_5_epochs_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_arabic_english_finetuned_npomo_english_5_epochs_pipeline` is a English model originally trained by UnassumingOwl.
+
+{:.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/opus_maltese_arabic_english_finetuned_npomo_english_5_epochs_pipeline_en_5.5.0_3.0_1725865355249.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_arabic_english_finetuned_npomo_english_5_epochs_pipeline_en_5.5.0_3.0_1725865355249.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
+
+pipeline = PretrainedPipeline("opus_maltese_arabic_english_finetuned_npomo_english_5_epochs_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_arabic_english_finetuned_npomo_english_5_epochs_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_arabic_english_finetuned_npomo_english_5_epochs_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|528.5 MB|
+
+## References
+
+https://huggingface.co/UnassumingOwl/opus-mt-ar-en-finetuned-npomo-en-5-epochs
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_english_german_bds_en.md b/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_english_german_bds_en.md
new file mode 100644
index 00000000000000..d85702a4bbe9a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_english_german_bds_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_german_bds MarianTransformer from Anhptp
+author: John Snow Labs
+name: opus_maltese_english_german_bds
+date: 2024-09-09
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_german_bds` is a English model originally trained by Anhptp.
+
+{:.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/opus_maltese_english_german_bds_en_5.5.0_3.0_1725840268583.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_german_bds_en_5.5.0_3.0_1725840268583.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_german_bds","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_german_bds","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_german_bds|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|499.4 MB|
+
+## References
+
+https://huggingface.co/Anhptp/opus-mt-en-de-BDS
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_english_italian_finetuned_4600_english_tonga_tonga_islands_italian_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_english_italian_finetuned_4600_english_tonga_tonga_islands_italian_pipeline_en.md
new file mode 100644
index 00000000000000..ed17ff8d49549b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_english_italian_finetuned_4600_english_tonga_tonga_islands_italian_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English opus_maltese_english_italian_finetuned_4600_english_tonga_tonga_islands_italian_pipeline pipeline MarianTransformer from VFiona
+author: John Snow Labs
+name: opus_maltese_english_italian_finetuned_4600_english_tonga_tonga_islands_italian_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_italian_finetuned_4600_english_tonga_tonga_islands_italian_pipeline` is a English model originally trained by VFiona.
+
+{:.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/opus_maltese_english_italian_finetuned_4600_english_tonga_tonga_islands_italian_pipeline_en_5.5.0_3.0_1725865173002.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_italian_finetuned_4600_english_tonga_tonga_islands_italian_pipeline_en_5.5.0_3.0_1725865173002.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
+
+pipeline = PretrainedPipeline("opus_maltese_english_italian_finetuned_4600_english_tonga_tonga_islands_italian_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("opus_maltese_english_italian_finetuned_4600_english_tonga_tonga_islands_italian_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_italian_finetuned_4600_english_tonga_tonga_islands_italian_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|623.4 MB|
+
+## References
+
+https://huggingface.co/VFiona/opus-mt-en-it-finetuned_4600-en-to-it
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_darren628_en.md b/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_darren628_en.md
new file mode 100644
index 00000000000000..6e8c54715e6fad
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_darren628_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_darren628 MarianTransformer from Darren628
+author: John Snow Labs
+name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_darren628
+date: 2024-09-09
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_darren628` is a English model originally trained by Darren628.
+
+{:.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/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_darren628_en_5.5.0_3.0_1725864210183.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_darren628_en_5.5.0_3.0_1725864210183.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_darren628","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_darren628","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_darren628|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.6 MB|
+
+## References
+
+https://huggingface.co/Darren628/opus-mt-en-ro-finetuned-en-to-ro
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_lariskelmer_en.md b/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_lariskelmer_en.md
new file mode 100644
index 00000000000000..2d02cc4f86f5ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_lariskelmer_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_lariskelmer MarianTransformer from lariskelmer
+author: John Snow Labs
+name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_lariskelmer
+date: 2024-09-09
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_lariskelmer` is a English model originally trained by lariskelmer.
+
+{:.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/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_lariskelmer_en_5.5.0_3.0_1725840474663.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_lariskelmer_en_5.5.0_3.0_1725840474663.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_lariskelmer","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_lariskelmer","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_romanian_lariskelmer|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.6 MB|
+
+## References
+
+https://huggingface.co/lariskelmer/opus-mt-en-ro-finetuned-en-to-ro
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_welsh_en.md b/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_welsh_en.md
new file mode 100644
index 00000000000000..312b4fa3fb2aa3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_welsh_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_welsh MarianTransformer from theojolliffe
+author: John Snow Labs
+name: opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_welsh
+date: 2024-09-09
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_welsh` is a English model originally trained by theojolliffe.
+
+{:.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/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_welsh_en_5.5.0_3.0_1725865654782.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_welsh_en_5.5.0_3.0_1725865654782.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_welsh","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_welsh","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_romanian_finetuned_english_tonga_tonga_islands_welsh|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|508.4 MB|
+
+## References
+
+https://huggingface.co/theojolliffe/opus-mt-en-ro-finetuned-en-to-cy
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_english_vietnamese_finetuned_eng_tonga_tonga_islands_vietnamese_en.md b/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_english_vietnamese_finetuned_eng_tonga_tonga_islands_vietnamese_en.md
new file mode 100644
index 00000000000000..9102d17dca88a5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_english_vietnamese_finetuned_eng_tonga_tonga_islands_vietnamese_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_english_vietnamese_finetuned_eng_tonga_tonga_islands_vietnamese MarianTransformer from callmeJ
+author: John Snow Labs
+name: opus_maltese_english_vietnamese_finetuned_eng_tonga_tonga_islands_vietnamese
+date: 2024-09-09
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_english_vietnamese_finetuned_eng_tonga_tonga_islands_vietnamese` is a English model originally trained by callmeJ.
+
+{:.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/opus_maltese_english_vietnamese_finetuned_eng_tonga_tonga_islands_vietnamese_en_5.5.0_3.0_1725863062153.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_english_vietnamese_finetuned_eng_tonga_tonga_islands_vietnamese_en_5.5.0_3.0_1725863062153.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_english_vietnamese_finetuned_eng_tonga_tonga_islands_vietnamese","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_english_vietnamese_finetuned_eng_tonga_tonga_islands_vietnamese","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_english_vietnamese_finetuned_eng_tonga_tonga_islands_vietnamese|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|474.6 MB|
+
+## References
+
+https://huggingface.co/callmeJ/opus-mt-en-vi-finetuned-eng-to-vie
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_ft_v3_3_epochs_en.md b/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_ft_v3_3_epochs_en.md
new file mode 100644
index 00000000000000..b65043378ef5bf
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_ft_v3_3_epochs_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_ft_v3_3_epochs MarianTransformer from abdiharyadi
+author: John Snow Labs
+name: opus_maltese_ft_v3_3_epochs
+date: 2024-09-09
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_ft_v3_3_epochs` is a English model originally trained by abdiharyadi.
+
+{:.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/opus_maltese_ft_v3_3_epochs_en_5.5.0_3.0_1725840158731.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_ft_v3_3_epochs_en_5.5.0_3.0_1725840158731.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_ft_v3_3_epochs","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_ft_v3_3_epochs","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_ft_v3_3_epochs|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|482.1 MB|
+
+## References
+
+https://huggingface.co/abdiharyadi/opus-mt-ft-v3-3-epochs
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_indonesian_english_ccmatrix_norwegian_warmup_best_loss_en.md b/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_indonesian_english_ccmatrix_norwegian_warmup_best_loss_en.md
new file mode 100644
index 00000000000000..d7121d9feeec6d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_indonesian_english_ccmatrix_norwegian_warmup_best_loss_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_indonesian_english_ccmatrix_norwegian_warmup_best_loss MarianTransformer from yonathanstwn
+author: John Snow Labs
+name: opus_maltese_indonesian_english_ccmatrix_norwegian_warmup_best_loss
+date: 2024-09-09
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_indonesian_english_ccmatrix_norwegian_warmup_best_loss` is a English model originally trained by yonathanstwn.
+
+{:.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/opus_maltese_indonesian_english_ccmatrix_norwegian_warmup_best_loss_en_5.5.0_3.0_1725840101430.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_indonesian_english_ccmatrix_norwegian_warmup_best_loss_en_5.5.0_3.0_1725840101430.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_indonesian_english_ccmatrix_norwegian_warmup_best_loss","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_indonesian_english_ccmatrix_norwegian_warmup_best_loss","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_indonesian_english_ccmatrix_norwegian_warmup_best_loss|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|480.2 MB|
+
+## References
+
+https://huggingface.co/yonathanstwn/opus-mt-id-en-ccmatrix-no-warmup-best-loss
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_korean_english_finetuned_english_tonga_tonga_islands_korean_lizzybennet_en.md b/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_korean_english_finetuned_english_tonga_tonga_islands_korean_lizzybennet_en.md
new file mode 100644
index 00000000000000..2b207c2528aa5f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_korean_english_finetuned_english_tonga_tonga_islands_korean_lizzybennet_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_korean_english_finetuned_english_tonga_tonga_islands_korean_lizzybennet MarianTransformer from LizzyBennet
+author: John Snow Labs
+name: opus_maltese_korean_english_finetuned_english_tonga_tonga_islands_korean_lizzybennet
+date: 2024-09-09
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_korean_english_finetuned_english_tonga_tonga_islands_korean_lizzybennet` is a English model originally trained by LizzyBennet.
+
+{:.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/opus_maltese_korean_english_finetuned_english_tonga_tonga_islands_korean_lizzybennet_en_5.5.0_3.0_1725840698805.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_korean_english_finetuned_english_tonga_tonga_islands_korean_lizzybennet_en_5.5.0_3.0_1725840698805.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_korean_english_finetuned_english_tonga_tonga_islands_korean_lizzybennet","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_korean_english_finetuned_english_tonga_tonga_islands_korean_lizzybennet","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_korean_english_finetuned_english_tonga_tonga_islands_korean_lizzybennet|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|540.6 MB|
+
+## References
+
+https://huggingface.co/LizzyBennet/opus-mt-ko-en-finetuned-en-to-ko
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_dentikka_en.md b/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_dentikka_en.md
new file mode 100644
index 00000000000000..6f2324dd519aa7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_dentikka_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_dentikka MarianTransformer from Dentikka
+author: John Snow Labs
+name: opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_dentikka
+date: 2024-09-09
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_dentikka` is a English model originally trained by Dentikka.
+
+{:.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/opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_dentikka_en_5.5.0_3.0_1725840243960.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_dentikka_en_5.5.0_3.0_1725840243960.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_dentikka","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_dentikka","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|opus_maltese_russian_english_finetuned_russian_tonga_tonga_islands_english_dentikka|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|526.4 MB|
+
+## References
+
+https://huggingface.co/Dentikka/opus-mt-ru-en-finetuned-ru-to-en
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-partypress_multilingual_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-09-partypress_multilingual_pipeline_xx.md
new file mode 100644
index 00000000000000..eb73de0cc0a745
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-partypress_multilingual_pipeline_xx.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Multilingual partypress_multilingual_pipeline pipeline BertForSequenceClassification from partypress
+author: John Snow Labs
+name: partypress_multilingual_pipeline
+date: 2024-09-09
+tags: [xx, open_source, pipeline, onnx]
+task: Text Classification
+language: xx
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`partypress_multilingual_pipeline` is a Multilingual model originally trained by partypress.
+
+{:.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/partypress_multilingual_pipeline_xx_5.5.0_3.0_1725856679826.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/partypress_multilingual_pipeline_xx_5.5.0_3.0_1725856679826.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
+
+pipeline = PretrainedPipeline("partypress_multilingual_pipeline", lang = "xx")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("partypress_multilingual_pipeline", lang = "xx")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|partypress_multilingual_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|xx|
+|Size:|667.4 MB|
+
+## References
+
+https://huggingface.co/partypress/partypress-multilingual
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-perovaz_portuguese_breton_classifier_pt.md b/docs/_posts/ahmedlone127/2024-09-09-perovaz_portuguese_breton_classifier_pt.md
new file mode 100644
index 00000000000000..edd8fb656eea74
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-perovaz_portuguese_breton_classifier_pt.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Portuguese perovaz_portuguese_breton_classifier BertForSequenceClassification from Bastao
+author: John Snow Labs
+name: perovaz_portuguese_breton_classifier
+date: 2024-09-09
+tags: [pt, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: pt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`perovaz_portuguese_breton_classifier` is a Portuguese model originally trained by Bastao.
+
+{:.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/perovaz_portuguese_breton_classifier_pt_5.5.0_3.0_1725852821658.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/perovaz_portuguese_breton_classifier_pt_5.5.0_3.0_1725852821658.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("perovaz_portuguese_breton_classifier","pt") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("perovaz_portuguese_breton_classifier", "pt")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|perovaz_portuguese_breton_classifier|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|pt|
+|Size:|16.7 MB|
+
+## References
+
+https://huggingface.co/Bastao/PeroVaz_PT-BR_Classifier
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-petbert_en.md b/docs/_posts/ahmedlone127/2024-09-09-petbert_en.md
new file mode 100644
index 00000000000000..87cf179fe1d96f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-petbert_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English petbert BertEmbeddings from SAVSNET
+author: John Snow Labs
+name: petbert
+date: 2024-09-09
+tags: [en, open_source, onnx, embeddings, bert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`petbert` is a English model originally trained by SAVSNET.
+
+{:.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/petbert_en_5.5.0_3.0_1725881926505.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/petbert_en_5.5.0_3.0_1725881926505.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = BertEmbeddings.pretrained("petbert","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = BertEmbeddings.pretrained("petbert","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|petbert|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[bert]|
+|Language:|en|
+|Size:|403.1 MB|
+
+## References
+
+https://huggingface.co/SAVSNET/PetBERT
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-portuguese_finegrained_few_shot_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-portuguese_finegrained_few_shot_pipeline_en.md
new file mode 100644
index 00000000000000..f286e5819740a2
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-portuguese_finegrained_few_shot_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English portuguese_finegrained_few_shot_pipeline pipeline XlmRoBertaForSequenceClassification from edwardgowsmith
+author: John Snow Labs
+name: portuguese_finegrained_few_shot_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`portuguese_finegrained_few_shot_pipeline` is a English model originally trained by edwardgowsmith.
+
+{:.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/portuguese_finegrained_few_shot_pipeline_en_5.5.0_3.0_1725870903715.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/portuguese_finegrained_few_shot_pipeline_en_5.5.0_3.0_1725870903715.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
+
+pipeline = PretrainedPipeline("portuguese_finegrained_few_shot_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("portuguese_finegrained_few_shot_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|portuguese_finegrained_few_shot_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|783.5 MB|
+
+## References
+
+https://huggingface.co/edwardgowsmith/pt-finegrained-few-shot
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-q2d_re_5_en.md b/docs/_posts/ahmedlone127/2024-09-09-q2d_re_5_en.md
new file mode 100644
index 00000000000000..504e3cb2c899af
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-q2d_re_5_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English q2d_re_5 MPNetEmbeddings from ingeol
+author: John Snow Labs
+name: q2d_re_5
+date: 2024-09-09
+tags: [en, open_source, onnx, embeddings, mpnet]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+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.`q2d_re_5` is a English model originally trained by ingeol.
+
+{:.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/q2d_re_5_en_5.5.0_3.0_1725874128035.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/q2d_re_5_en_5.5.0_3.0_1725874128035.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+embeddings = MPNetEmbeddings.pretrained("q2d_re_5","en") \
+      .setInputCols(["document"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val embeddings = MPNetEmbeddings.pretrained("q2d_re_5","en") 
+    .setInputCols(Array("document")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|q2d_re_5|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.1 MB|
+
+## References
+
+https://huggingface.co/ingeol/q2d_re_5
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-qa_callback_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-qa_callback_pipeline_en.md
new file mode 100644
index 00000000000000..8f6b8a257d813c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-qa_callback_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qa_callback_pipeline pipeline DistilBertForQuestionAnswering from RachelLe
+author: John Snow Labs
+name: qa_callback_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_callback_pipeline` is a English model originally trained by RachelLe.
+
+{:.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/qa_callback_pipeline_en_5.5.0_3.0_1725876965655.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_callback_pipeline_en_5.5.0_3.0_1725876965655.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
+
+pipeline = PretrainedPipeline("qa_callback_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qa_callback_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_callback_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.3 MB|
+
+## References
+
+https://huggingface.co/RachelLe/qa_callback
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-qa_model101_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-qa_model101_pipeline_en.md
new file mode 100644
index 00000000000000..fba097a5f93971
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-qa_model101_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English qa_model101_pipeline pipeline DistilBertForQuestionAnswering from jakeoko
+author: John Snow Labs
+name: qa_model101_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_model101_pipeline` is a English model originally trained by jakeoko.
+
+{:.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/qa_model101_pipeline_en_5.5.0_3.0_1725869332658.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_model101_pipeline_en_5.5.0_3.0_1725869332658.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
+
+pipeline = PretrainedPipeline("qa_model101_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qa_model101_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_model101_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/jakeoko/qa_model101
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-qa_model_bytesizedllm_en.md b/docs/_posts/ahmedlone127/2024-09-09-qa_model_bytesizedllm_en.md
new file mode 100644
index 00000000000000..ccdce0c948fee4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-qa_model_bytesizedllm_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English qa_model_bytesizedllm DistilBertForQuestionAnswering from bytesizedllm
+author: John Snow Labs
+name: qa_model_bytesizedllm
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_model_bytesizedllm` is a English model originally trained by bytesizedllm.
+
+{:.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/qa_model_bytesizedllm_en_5.5.0_3.0_1725869313333.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_model_bytesizedllm_en_5.5.0_3.0_1725869313333.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("qa_model_bytesizedllm","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("qa_model_bytesizedllm", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qa_model_bytesizedllm|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/bytesizedllm/qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-qqp_microsoft_deberta_v3_large_seed_1_en.md b/docs/_posts/ahmedlone127/2024-09-09-qqp_microsoft_deberta_v3_large_seed_1_en.md
new file mode 100644
index 00000000000000..359bff3d1a3090
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-qqp_microsoft_deberta_v3_large_seed_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English qqp_microsoft_deberta_v3_large_seed_1 DeBertaForSequenceClassification from utahnlp
+author: John Snow Labs
+name: qqp_microsoft_deberta_v3_large_seed_1
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qqp_microsoft_deberta_v3_large_seed_1` is a English model originally trained by utahnlp.
+
+{:.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/qqp_microsoft_deberta_v3_large_seed_1_en_5.5.0_3.0_1725879299942.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qqp_microsoft_deberta_v3_large_seed_1_en_5.5.0_3.0_1725879299942.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("qqp_microsoft_deberta_v3_large_seed_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("qqp_microsoft_deberta_v3_large_seed_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qqp_microsoft_deberta_v3_large_seed_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/utahnlp/qqp_microsoft_deberta-v3-large_seed-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-qqp_microsoft_deberta_v3_large_seed_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-qqp_microsoft_deberta_v3_large_seed_1_pipeline_en.md
new file mode 100644
index 00000000000000..e84bee5674f50a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-qqp_microsoft_deberta_v3_large_seed_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English qqp_microsoft_deberta_v3_large_seed_1_pipeline pipeline DeBertaForSequenceClassification from utahnlp
+author: John Snow Labs
+name: qqp_microsoft_deberta_v3_large_seed_1_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qqp_microsoft_deberta_v3_large_seed_1_pipeline` is a English model originally trained by utahnlp.
+
+{:.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/qqp_microsoft_deberta_v3_large_seed_1_pipeline_en_5.5.0_3.0_1725879390702.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qqp_microsoft_deberta_v3_large_seed_1_pipeline_en_5.5.0_3.0_1725879390702.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
+
+pipeline = PretrainedPipeline("qqp_microsoft_deberta_v3_large_seed_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qqp_microsoft_deberta_v3_large_seed_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qqp_microsoft_deberta_v3_large_seed_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/utahnlp/qqp_microsoft_deberta-v3-large_seed-1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-qqp_microsoft_deberta_v3_large_seed_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-qqp_microsoft_deberta_v3_large_seed_2_pipeline_en.md
new file mode 100644
index 00000000000000..9a182e2b811968
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-qqp_microsoft_deberta_v3_large_seed_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English qqp_microsoft_deberta_v3_large_seed_2_pipeline pipeline DeBertaForSequenceClassification from utahnlp
+author: John Snow Labs
+name: qqp_microsoft_deberta_v3_large_seed_2_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qqp_microsoft_deberta_v3_large_seed_2_pipeline` is a English model originally trained by utahnlp.
+
+{:.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/qqp_microsoft_deberta_v3_large_seed_2_pipeline_en_5.5.0_3.0_1725880465255.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qqp_microsoft_deberta_v3_large_seed_2_pipeline_en_5.5.0_3.0_1725880465255.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
+
+pipeline = PretrainedPipeline("qqp_microsoft_deberta_v3_large_seed_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("qqp_microsoft_deberta_v3_large_seed_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|qqp_microsoft_deberta_v3_large_seed_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/utahnlp/qqp_microsoft_deberta-v3-large_seed-2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-question_answering_model_vishnun0027_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-question_answering_model_vishnun0027_pipeline_en.md
new file mode 100644
index 00000000000000..783f45e74098f4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-question_answering_model_vishnun0027_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English question_answering_model_vishnun0027_pipeline pipeline DistilBertForQuestionAnswering from vishnun0027
+author: John Snow Labs
+name: question_answering_model_vishnun0027_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`question_answering_model_vishnun0027_pipeline` is a English model originally trained by vishnun0027.
+
+{:.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/question_answering_model_vishnun0027_pipeline_en_5.5.0_3.0_1725877088338.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/question_answering_model_vishnun0027_pipeline_en_5.5.0_3.0_1725877088338.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
+
+pipeline = PretrainedPipeline("question_answering_model_vishnun0027_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("question_answering_model_vishnun0027_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|question_answering_model_vishnun0027_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/vishnun0027/Question_answering_model
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-question_anwsering_en.md b/docs/_posts/ahmedlone127/2024-09-09-question_anwsering_en.md
new file mode 100644
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@@ -0,0 +1,86 @@
+---
+layout: model
+title: English question_anwsering DistilBertForQuestionAnswering from Yeji-Seong
+author: John Snow Labs
+name: question_anwsering
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`question_anwsering` is a English model originally trained by Yeji-Seong.
+
+{:.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/question_anwsering_en_5.5.0_3.0_1725868864076.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/question_anwsering_en_5.5.0_3.0_1725868864076.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("question_anwsering","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("question_anwsering", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|question_anwsering|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Yeji-Seong/question-anwsering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-recipes_trainer_wwm_n_sentences_per_recipe_3_sep_true_en.md b/docs/_posts/ahmedlone127/2024-09-09-recipes_trainer_wwm_n_sentences_per_recipe_3_sep_true_en.md
new file mode 100644
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+---
+layout: model
+title: English recipes_trainer_wwm_n_sentences_per_recipe_3_sep_true CamemBertEmbeddings from comartinez
+author: John Snow Labs
+name: recipes_trainer_wwm_n_sentences_per_recipe_3_sep_true
+date: 2024-09-09
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`recipes_trainer_wwm_n_sentences_per_recipe_3_sep_true` is a English model originally trained by comartinez.
+
+{:.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/recipes_trainer_wwm_n_sentences_per_recipe_3_sep_true_en_5.5.0_3.0_1725852037159.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/recipes_trainer_wwm_n_sentences_per_recipe_3_sep_true_en_5.5.0_3.0_1725852037159.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("recipes_trainer_wwm_n_sentences_per_recipe_3_sep_true","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("recipes_trainer_wwm_n_sentences_per_recipe_3_sep_true","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|recipes_trainer_wwm_n_sentences_per_recipe_3_sep_true|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|412.3 MB|
+
+## References
+
+https://huggingface.co/comartinez/recipes-trainer-wwm_n_sentences_per_recipe_3_sep_True
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-recipes_trainer_wwm_n_sentences_per_recipe_3_sep_true_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-recipes_trainer_wwm_n_sentences_per_recipe_3_sep_true_pipeline_en.md
new file mode 100644
index 00000000000000..23cfa4c97c8d8c
--- /dev/null
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@@ -0,0 +1,70 @@
+---
+layout: model
+title: English recipes_trainer_wwm_n_sentences_per_recipe_3_sep_true_pipeline pipeline CamemBertEmbeddings from comartinez
+author: John Snow Labs
+name: recipes_trainer_wwm_n_sentences_per_recipe_3_sep_true_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`recipes_trainer_wwm_n_sentences_per_recipe_3_sep_true_pipeline` is a English model originally trained by comartinez.
+
+{:.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/recipes_trainer_wwm_n_sentences_per_recipe_3_sep_true_pipeline_en_5.5.0_3.0_1725852057099.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/recipes_trainer_wwm_n_sentences_per_recipe_3_sep_true_pipeline_en_5.5.0_3.0_1725852057099.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
+
+pipeline = PretrainedPipeline("recipes_trainer_wwm_n_sentences_per_recipe_3_sep_true_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("recipes_trainer_wwm_n_sentences_per_recipe_3_sep_true_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|recipes_trainer_wwm_n_sentences_per_recipe_3_sep_true_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|412.3 MB|
+
+## References
+
+https://huggingface.co/comartinez/recipes-trainer-wwm_n_sentences_per_recipe_3_sep_True
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-results_alexhv_en.md b/docs/_posts/ahmedlone127/2024-09-09-results_alexhv_en.md
new file mode 100644
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--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-results_alexhv_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English results_alexhv DistilBertForQuestionAnswering from Alexhv
+author: John Snow Labs
+name: results_alexhv
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_alexhv` is a English model originally trained by Alexhv.
+
+{:.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/results_alexhv_en_5.5.0_3.0_1725869219101.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_alexhv_en_5.5.0_3.0_1725869219101.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("results_alexhv","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("results_alexhv", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_alexhv|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/Alexhv/results
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-results_alexhv_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-results_alexhv_pipeline_en.md
new file mode 100644
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--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-results_alexhv_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English results_alexhv_pipeline pipeline DistilBertForQuestionAnswering from Alexhv
+author: John Snow Labs
+name: results_alexhv_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_alexhv_pipeline` is a English model originally trained by Alexhv.
+
+{:.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/results_alexhv_pipeline_en_5.5.0_3.0_1725869231151.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_alexhv_pipeline_en_5.5.0_3.0_1725869231151.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
+
+pipeline = PretrainedPipeline("results_alexhv_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("results_alexhv_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_alexhv_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|243.8 MB|
+
+## References
+
+https://huggingface.co/Alexhv/results
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-robbert_dutch_base_squad_dutch_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-robbert_dutch_base_squad_dutch_pipeline_en.md
new file mode 100644
index 00000000000000..907e54b9c2aaf5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-robbert_dutch_base_squad_dutch_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English robbert_dutch_base_squad_dutch_pipeline pipeline RoBertaForQuestionAnswering from Nadav
+author: John Snow Labs
+name: robbert_dutch_base_squad_dutch_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`robbert_dutch_base_squad_dutch_pipeline` is a English model originally trained by Nadav.
+
+{:.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/robbert_dutch_base_squad_dutch_pipeline_en_5.5.0_3.0_1725876253852.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/robbert_dutch_base_squad_dutch_pipeline_en_5.5.0_3.0_1725876253852.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
+
+pipeline = PretrainedPipeline("robbert_dutch_base_squad_dutch_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("robbert_dutch_base_squad_dutch_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|robbert_dutch_base_squad_dutch_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|435.7 MB|
+
+## References
+
+https://huggingface.co/Nadav/robbert-dutch-base-squad-nl
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-roberta_base_dofla_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-roberta_base_dofla_pipeline_en.md
new file mode 100644
index 00000000000000..f8ad82acb42ea7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-roberta_base_dofla_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_base_dofla_pipeline pipeline RoBertaForQuestionAnswering from Dofla
+author: John Snow Labs
+name: roberta_base_dofla_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_dofla_pipeline` is a English model originally trained by Dofla.
+
+{:.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/roberta_base_dofla_pipeline_en_5.5.0_3.0_1725867048990.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_dofla_pipeline_en_5.5.0_3.0_1725867048990.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
+
+pipeline = PretrainedPipeline("roberta_base_dofla_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_dofla_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_dofla_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|461.7 MB|
+
+## References
+
+https://huggingface.co/Dofla/roberta-base
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-roberta_base_finetuned_hotpot_qa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-roberta_base_finetuned_hotpot_qa_pipeline_en.md
new file mode 100644
index 00000000000000..9fce8f5eb31aed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-roberta_base_finetuned_hotpot_qa_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_base_finetuned_hotpot_qa_pipeline pipeline RoBertaForQuestionAnswering from vish88
+author: John Snow Labs
+name: roberta_base_finetuned_hotpot_qa_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_finetuned_hotpot_qa_pipeline` is a English model originally trained by vish88.
+
+{:.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/roberta_base_finetuned_hotpot_qa_pipeline_en_5.5.0_3.0_1725867184334.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_hotpot_qa_pipeline_en_5.5.0_3.0_1725867184334.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
+
+pipeline = PretrainedPipeline("roberta_base_finetuned_hotpot_qa_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_finetuned_hotpot_qa_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_finetuned_hotpot_qa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.9 MB|
+
+## References
+
+https://huggingface.co/vish88/roberta-base-finetuned-hotpot_qa
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-roberta_base_finetuned_squadv2_vubacktracking_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-roberta_base_finetuned_squadv2_vubacktracking_pipeline_en.md
new file mode 100644
index 00000000000000..6aefc66968f727
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-roberta_base_finetuned_squadv2_vubacktracking_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_base_finetuned_squadv2_vubacktracking_pipeline pipeline RoBertaForQuestionAnswering from vubacktracking
+author: John Snow Labs
+name: roberta_base_finetuned_squadv2_vubacktracking_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_finetuned_squadv2_vubacktracking_pipeline` is a English model originally trained by vubacktracking.
+
+{:.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/roberta_base_finetuned_squadv2_vubacktracking_pipeline_en_5.5.0_3.0_1725876314878.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_squadv2_vubacktracking_pipeline_en_5.5.0_3.0_1725876314878.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
+
+pipeline = PretrainedPipeline("roberta_base_finetuned_squadv2_vubacktracking_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_finetuned_squadv2_vubacktracking_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_finetuned_squadv2_vubacktracking_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|462.0 MB|
+
+## References
+
+https://huggingface.co/vubacktracking/roberta-base-finetuned-squadv2
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-roberta_base_mod_quoref_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-roberta_base_mod_quoref_pipeline_en.md
new file mode 100644
index 00000000000000..d65cb616b2b56d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-roberta_base_mod_quoref_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_base_mod_quoref_pipeline pipeline RoBertaForQuestionAnswering from damapika
+author: John Snow Labs
+name: roberta_base_mod_quoref_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_mod_quoref_pipeline` is a English model originally trained by damapika.
+
+{:.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/roberta_base_mod_quoref_pipeline_en_5.5.0_3.0_1725876071903.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_mod_quoref_pipeline_en_5.5.0_3.0_1725876071903.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
+
+pipeline = PretrainedPipeline("roberta_base_mod_quoref_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_mod_quoref_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_mod_quoref_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|464.1 MB|
+
+## References
+
+https://huggingface.co/damapika/roberta-base_mod_quoref
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-roberta_base_squad2_squad_k5_e3_full_finetune_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-roberta_base_squad2_squad_k5_e3_full_finetune_pipeline_en.md
new file mode 100644
index 00000000000000..2c85889a84f74e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-roberta_base_squad2_squad_k5_e3_full_finetune_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_base_squad2_squad_k5_e3_full_finetune_pipeline pipeline RoBertaForQuestionAnswering from umarzein
+author: John Snow Labs
+name: roberta_base_squad2_squad_k5_e3_full_finetune_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_squad2_squad_k5_e3_full_finetune_pipeline` is a English model originally trained by umarzein.
+
+{:.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/roberta_base_squad2_squad_k5_e3_full_finetune_pipeline_en_5.5.0_3.0_1725875996954.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_squad2_squad_k5_e3_full_finetune_pipeline_en_5.5.0_3.0_1725875996954.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
+
+pipeline = PretrainedPipeline("roberta_base_squad2_squad_k5_e3_full_finetune_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_squad2_squad_k5_e3_full_finetune_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_squad2_squad_k5_e3_full_finetune_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.7 MB|
+
+## References
+
+https://huggingface.co/umarzein/roberta-base-squad2-squad-k5-e3-full-finetune
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-roberta_base_squad_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-roberta_base_squad_v2_pipeline_en.md
new file mode 100644
index 00000000000000..03649feb3391be
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-roberta_base_squad_v2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_base_squad_v2_pipeline pipeline RoBertaForQuestionAnswering from etweedy
+author: John Snow Labs
+name: roberta_base_squad_v2_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_squad_v2_pipeline` is a English model originally trained by etweedy.
+
+{:.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/roberta_base_squad_v2_pipeline_en_5.5.0_3.0_1725866754991.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_squad_v2_pipeline_en_5.5.0_3.0_1725866754991.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
+
+pipeline = PretrainedPipeline("roberta_base_squad_v2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_base_squad_v2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_base_squad_v2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|462.6 MB|
+
+## References
+
+https://huggingface.co/etweedy/roberta-base-squad-v2
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-roberta_crypto_profiling_task1_deberta_en.md b/docs/_posts/ahmedlone127/2024-09-09-roberta_crypto_profiling_task1_deberta_en.md
new file mode 100644
index 00000000000000..11ac4d0e5b847b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-roberta_crypto_profiling_task1_deberta_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_crypto_profiling_task1_deberta DeBertaForSequenceClassification from pabagcha
+author: John Snow Labs
+name: roberta_crypto_profiling_task1_deberta
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_crypto_profiling_task1_deberta` is a English model originally trained by pabagcha.
+
+{:.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/roberta_crypto_profiling_task1_deberta_en_5.5.0_3.0_1725879920390.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_crypto_profiling_task1_deberta_en_5.5.0_3.0_1725879920390.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("roberta_crypto_profiling_task1_deberta","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("roberta_crypto_profiling_task1_deberta", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_crypto_profiling_task1_deberta|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/pabagcha/roberta_crypto_profiling_task1_deberta
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-roberta_finetuned_squad_shortcut_token_before_answer_start_en.md b/docs/_posts/ahmedlone127/2024-09-09-roberta_finetuned_squad_shortcut_token_before_answer_start_en.md
new file mode 100644
index 00000000000000..84ca19c614f130
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-roberta_finetuned_squad_shortcut_token_before_answer_start_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English roberta_finetuned_squad_shortcut_token_before_answer_start RoBertaForQuestionAnswering from TimoImhof
+author: John Snow Labs
+name: roberta_finetuned_squad_shortcut_token_before_answer_start
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_squad_shortcut_token_before_answer_start` is a English model originally trained by TimoImhof.
+
+{:.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/roberta_finetuned_squad_shortcut_token_before_answer_start_en_5.5.0_3.0_1725866810442.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_squad_shortcut_token_before_answer_start_en_5.5.0_3.0_1725866810442.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_squad_shortcut_token_before_answer_start","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_squad_shortcut_token_before_answer_start", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_finetuned_squad_shortcut_token_before_answer_start|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|463.6 MB|
+
+## References
+
+https://huggingface.co/TimoImhof/roberta-finetuned-squad-shortcut-token-before-answer-start
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-roberta_finetuned_squadcovid_en.md b/docs/_posts/ahmedlone127/2024-09-09-roberta_finetuned_squadcovid_en.md
new file mode 100644
index 00000000000000..4d3f8f2fcaf398
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-roberta_finetuned_squadcovid_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English roberta_finetuned_squadcovid RoBertaForQuestionAnswering from Rahul13
+author: John Snow Labs
+name: roberta_finetuned_squadcovid
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_squadcovid` is a English model originally trained by Rahul13.
+
+{:.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/roberta_finetuned_squadcovid_en_5.5.0_3.0_1725875775639.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_squadcovid_en_5.5.0_3.0_1725875775639.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_squadcovid","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_squadcovid", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_finetuned_squadcovid|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|463.9 MB|
+
+## References
+
+https://huggingface.co/Rahul13/roberta-finetuned-squadcovid
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-roberta_finetuned_subjqa_chennaiqa_expanded_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-roberta_finetuned_subjqa_chennaiqa_expanded_pipeline_en.md
new file mode 100644
index 00000000000000..4ca107384692d4
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-roberta_finetuned_subjqa_chennaiqa_expanded_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_finetuned_subjqa_chennaiqa_expanded_pipeline pipeline RoBertaForQuestionAnswering from aditi2212
+author: John Snow Labs
+name: roberta_finetuned_subjqa_chennaiqa_expanded_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_subjqa_chennaiqa_expanded_pipeline` is a English model originally trained by aditi2212.
+
+{:.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/roberta_finetuned_subjqa_chennaiqa_expanded_pipeline_en_5.5.0_3.0_1725876116132.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_chennaiqa_expanded_pipeline_en_5.5.0_3.0_1725876116132.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
+
+pipeline = PretrainedPipeline("roberta_finetuned_subjqa_chennaiqa_expanded_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_finetuned_subjqa_chennaiqa_expanded_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_finetuned_subjqa_chennaiqa_expanded_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.6 MB|
+
+## References
+
+https://huggingface.co/aditi2212/roberta-finetuned-subjqa-ChennaiQA-expanded
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-roberta_finetuned_subjqa_movies_2_malizade_en.md b/docs/_posts/ahmedlone127/2024-09-09-roberta_finetuned_subjqa_movies_2_malizade_en.md
new file mode 100644
index 00000000000000..42c36f920fb03d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-roberta_finetuned_subjqa_movies_2_malizade_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English roberta_finetuned_subjqa_movies_2_malizade RoBertaForQuestionAnswering from malizade
+author: John Snow Labs
+name: roberta_finetuned_subjqa_movies_2_malizade
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_subjqa_movies_2_malizade` is a English model originally trained by malizade.
+
+{:.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/roberta_finetuned_subjqa_movies_2_malizade_en_5.5.0_3.0_1725866595226.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_malizade_en_5.5.0_3.0_1725866595226.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_subjqa_movies_2_malizade","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_subjqa_movies_2_malizade", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_finetuned_subjqa_movies_2_malizade|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|464.1 MB|
+
+## References
+
+https://huggingface.co/malizade/roberta-finetuned-subjqa-movies_2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-roberta_finetuned_subjqa_movies_2_malizade_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-roberta_finetuned_subjqa_movies_2_malizade_pipeline_en.md
new file mode 100644
index 00000000000000..fc7bd67e1cf5ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-roberta_finetuned_subjqa_movies_2_malizade_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_finetuned_subjqa_movies_2_malizade_pipeline pipeline RoBertaForQuestionAnswering from malizade
+author: John Snow Labs
+name: roberta_finetuned_subjqa_movies_2_malizade_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_subjqa_movies_2_malizade_pipeline` is a English model originally trained by malizade.
+
+{:.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/roberta_finetuned_subjqa_movies_2_malizade_pipeline_en_5.5.0_3.0_1725866620576.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_malizade_pipeline_en_5.5.0_3.0_1725866620576.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
+
+pipeline = PretrainedPipeline("roberta_finetuned_subjqa_movies_2_malizade_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_finetuned_subjqa_movies_2_malizade_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_finetuned_subjqa_movies_2_malizade_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|464.1 MB|
+
+## References
+
+https://huggingface.co/malizade/roberta-finetuned-subjqa-movies_2
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-roberta_finetuned_subjqa_movies_2_vishwasbhushanb_en.md b/docs/_posts/ahmedlone127/2024-09-09-roberta_finetuned_subjqa_movies_2_vishwasbhushanb_en.md
new file mode 100644
index 00000000000000..24f026fa35e494
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-roberta_finetuned_subjqa_movies_2_vishwasbhushanb_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English roberta_finetuned_subjqa_movies_2_vishwasbhushanb RoBertaForQuestionAnswering from VishwasBhushanB
+author: John Snow Labs
+name: roberta_finetuned_subjqa_movies_2_vishwasbhushanb
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_subjqa_movies_2_vishwasbhushanb` is a English model originally trained by VishwasBhushanB.
+
+{:.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/roberta_finetuned_subjqa_movies_2_vishwasbhushanb_en_5.5.0_3.0_1725876361534.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_vishwasbhushanb_en_5.5.0_3.0_1725876361534.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_subjqa_movies_2_vishwasbhushanb","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_subjqa_movies_2_vishwasbhushanb", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_finetuned_subjqa_movies_2_vishwasbhushanb|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|464.1 MB|
+
+## References
+
+https://huggingface.co/VishwasBhushanB/roberta-finetuned-subjqa-movies_2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-roberta_large_few_shot_k_1024_finetuned_squad_seed_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-roberta_large_few_shot_k_1024_finetuned_squad_seed_2_pipeline_en.md
new file mode 100644
index 00000000000000..64873dfa99ff9a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-roberta_large_few_shot_k_1024_finetuned_squad_seed_2_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_large_few_shot_k_1024_finetuned_squad_seed_2_pipeline pipeline RoBertaForQuestionAnswering from anas-awadalla
+author: John Snow Labs
+name: roberta_large_few_shot_k_1024_finetuned_squad_seed_2_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_few_shot_k_1024_finetuned_squad_seed_2_pipeline` is a English model originally trained by anas-awadalla.
+
+{:.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/roberta_large_few_shot_k_1024_finetuned_squad_seed_2_pipeline_en_5.5.0_3.0_1725875938340.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_few_shot_k_1024_finetuned_squad_seed_2_pipeline_en_5.5.0_3.0_1725875938340.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
+
+pipeline = PretrainedPipeline("roberta_large_few_shot_k_1024_finetuned_squad_seed_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_large_few_shot_k_1024_finetuned_squad_seed_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_few_shot_k_1024_finetuned_squad_seed_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/anas-awadalla/roberta-large-few-shot-k-1024-finetuned-squad-seed-2
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-roberta_large_squadv2_antoineblanot_en.md b/docs/_posts/ahmedlone127/2024-09-09-roberta_large_squadv2_antoineblanot_en.md
new file mode 100644
index 00000000000000..573b0c51ac2c71
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-roberta_large_squadv2_antoineblanot_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English roberta_large_squadv2_antoineblanot RoBertaForQuestionAnswering from AntoineBlanot
+author: John Snow Labs
+name: roberta_large_squadv2_antoineblanot
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_squadv2_antoineblanot` is a English model originally trained by AntoineBlanot.
+
+{:.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/roberta_large_squadv2_antoineblanot_en_5.5.0_3.0_1725867116728.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_squadv2_antoineblanot_en_5.5.0_3.0_1725867116728.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_large_squadv2_antoineblanot","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_large_squadv2_antoineblanot", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_squadv2_antoineblanot|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/AntoineBlanot/roberta-large-squadv2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-roberta_large_squadv2_antoineblanot_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-roberta_large_squadv2_antoineblanot_pipeline_en.md
new file mode 100644
index 00000000000000..4e08b0023eeeba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-roberta_large_squadv2_antoineblanot_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_large_squadv2_antoineblanot_pipeline pipeline RoBertaForQuestionAnswering from AntoineBlanot
+author: John Snow Labs
+name: roberta_large_squadv2_antoineblanot_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_squadv2_antoineblanot_pipeline` is a English model originally trained by AntoineBlanot.
+
+{:.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/roberta_large_squadv2_antoineblanot_pipeline_en_5.5.0_3.0_1725867183503.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_squadv2_antoineblanot_pipeline_en_5.5.0_3.0_1725867183503.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
+
+pipeline = PretrainedPipeline("roberta_large_squadv2_antoineblanot_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_large_squadv2_antoineblanot_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_large_squadv2_antoineblanot_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/AntoineBlanot/roberta-large-squadv2
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-roberta_mlm_marathi_pipeline_mr.md b/docs/_posts/ahmedlone127/2024-09-09-roberta_mlm_marathi_pipeline_mr.md
new file mode 100644
index 00000000000000..b63fa5167026ed
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-roberta_mlm_marathi_pipeline_mr.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Marathi roberta_mlm_marathi_pipeline pipeline RoBertaEmbeddings from deepampatel
+author: John Snow Labs
+name: roberta_mlm_marathi_pipeline
+date: 2024-09-09
+tags: [mr, open_source, pipeline, onnx]
+task: Embeddings
+language: mr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_mlm_marathi_pipeline` is a Marathi model originally trained by deepampatel.
+
+{:.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/roberta_mlm_marathi_pipeline_mr_5.5.0_3.0_1725860255569.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_mlm_marathi_pipeline_mr_5.5.0_3.0_1725860255569.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
+
+pipeline = PretrainedPipeline("roberta_mlm_marathi_pipeline", lang = "mr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_mlm_marathi_pipeline", lang = "mr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_mlm_marathi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|mr|
+|Size:|470.9 MB|
+
+## References
+
+https://huggingface.co/deepampatel/roberta-mlm-marathi
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-roberta_pubmed_en.md b/docs/_posts/ahmedlone127/2024-09-09-roberta_pubmed_en.md
new file mode 100644
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--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-roberta_pubmed_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English roberta_pubmed RoBertaEmbeddings from raynardj
+author: John Snow Labs
+name: roberta_pubmed
+date: 2024-09-09
+tags: [en, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_pubmed` is a English model originally trained by raynardj.
+
+{:.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/roberta_pubmed_en_5.5.0_3.0_1725883129738.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_pubmed_en_5.5.0_3.0_1725883129738.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("roberta_pubmed","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("roberta_pubmed","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_pubmed|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|en|
+|Size:|466.0 MB|
+
+## References
+
+https://huggingface.co/raynardj/roberta-pubmed
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-roberta_qa_base_squad2_tamil_qna_3e_en.md b/docs/_posts/ahmedlone127/2024-09-09-roberta_qa_base_squad2_tamil_qna_3e_en.md
new file mode 100644
index 00000000000000..7c112165479826
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-roberta_qa_base_squad2_tamil_qna_3e_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English roberta_qa_base_squad2_tamil_qna_3e RoBertaForQuestionAnswering from venkateshdas
+author: John Snow Labs
+name: roberta_qa_base_squad2_tamil_qna_3e
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_base_squad2_tamil_qna_3e` is a English model originally trained by venkateshdas.
+
+{:.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/roberta_qa_base_squad2_tamil_qna_3e_en_5.5.0_3.0_1725866897751.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_base_squad2_tamil_qna_3e_en_5.5.0_3.0_1725866897751.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_base_squad2_tamil_qna_3e","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_base_squad2_tamil_qna_3e", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_base_squad2_tamil_qna_3e|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|463.5 MB|
+
+## References
+
+https://huggingface.co/venkateshdas/roberta-base-squad2-ta-qna-roberta3e
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-roberta_qa_base_squad2_tamil_qna_3e_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-roberta_qa_base_squad2_tamil_qna_3e_pipeline_en.md
new file mode 100644
index 00000000000000..80a9df90ec1525
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-roberta_qa_base_squad2_tamil_qna_3e_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_base_squad2_tamil_qna_3e_pipeline pipeline RoBertaForQuestionAnswering from venkateshdas
+author: John Snow Labs
+name: roberta_qa_base_squad2_tamil_qna_3e_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_base_squad2_tamil_qna_3e_pipeline` is a English model originally trained by venkateshdas.
+
+{:.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/roberta_qa_base_squad2_tamil_qna_3e_pipeline_en_5.5.0_3.0_1725866921059.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_base_squad2_tamil_qna_3e_pipeline_en_5.5.0_3.0_1725866921059.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
+
+pipeline = PretrainedPipeline("roberta_qa_base_squad2_tamil_qna_3e_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_base_squad2_tamil_qna_3e_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_base_squad2_tamil_qna_3e_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|463.6 MB|
+
+## References
+
+https://huggingface.co/venkateshdas/roberta-base-squad2-ta-qna-roberta3e
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-roberta_qa_fpdm_soup_model_squad2.0_en.md b/docs/_posts/ahmedlone127/2024-09-09-roberta_qa_fpdm_soup_model_squad2.0_en.md
new file mode 100644
index 00000000000000..0e2015a0a1ad64
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-roberta_qa_fpdm_soup_model_squad2.0_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering Cased model (from AnonymousSub)
+author: John Snow Labs
+name: roberta_qa_fpdm_soup_model_squad2.0
+date: 2024-09-09
+tags: [en, open_source, roberta, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RobertaForQuestionAnswering  model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `fpdm_roberta_soup_model_squad2.0` is a English model originally trained by `AnonymousSub`.
+
+## 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/roberta_qa_fpdm_soup_model_squad2.0_en_5.5.0_3.0_1725866881514.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_fpdm_soup_model_squad2.0_en_5.5.0_3.0_1725866881514.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 = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_fpdm_soup_model_squad2.0","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_fpdm_soup_model_squad2.0","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_fpdm_soup_model_squad2.0|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|459.7 MB|
+
+## References
+
+References
+
+- https://huggingface.co/AnonymousSub/fpdm_roberta_soup_model_squad2.0
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-roberta_qa_model_10k_en.md b/docs/_posts/ahmedlone127/2024-09-09-roberta_qa_model_10k_en.md
new file mode 100644
index 00000000000000..c8574f1e2942e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-roberta_qa_model_10k_en.md
@@ -0,0 +1,92 @@
+---
+layout: model
+title: English RobertaForQuestionAnswering Cased model (from anablasi)
+author: John Snow Labs
+name: roberta_qa_model_10k
+date: 2024-09-09
+tags: [en, open_source, roberta, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RobertaForQuestionAnswering  model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `model_10k_qa` is a English model originally trained by `anablasi`.
+
+## 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/roberta_qa_model_10k_en_5.5.0_3.0_1725867010592.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_model_10k_en_5.5.0_3.0_1725867010592.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 = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_model_10k","en")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+    
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_model_10k","en")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+    
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_model_10k|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|466.4 MB|
+
+## References
+
+References
+
+- https://huggingface.co/anablasi/model_10k_qa
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-roberta_qa_rule_based_hier_triplet_shuffled_epochs_1_shard_1_squad2.0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-roberta_qa_rule_based_hier_triplet_shuffled_epochs_1_shard_1_squad2.0_pipeline_en.md
new file mode 100644
index 00000000000000..2ed3d02cc4c929
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-roberta_qa_rule_based_hier_triplet_shuffled_epochs_1_shard_1_squad2.0_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English roberta_qa_rule_based_hier_triplet_shuffled_epochs_1_shard_1_squad2.0_pipeline pipeline RoBertaForQuestionAnswering from AnonymousSub
+author: John Snow Labs
+name: roberta_qa_rule_based_hier_triplet_shuffled_epochs_1_shard_1_squad2.0_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_rule_based_hier_triplet_shuffled_epochs_1_shard_1_squad2.0_pipeline` is a English model originally trained by AnonymousSub.
+
+{:.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/roberta_qa_rule_based_hier_triplet_shuffled_epochs_1_shard_1_squad2.0_pipeline_en_5.5.0_3.0_1725866622358.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_rule_based_hier_triplet_shuffled_epochs_1_shard_1_squad2.0_pipeline_en_5.5.0_3.0_1725866622358.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
+
+pipeline = PretrainedPipeline("roberta_qa_rule_based_hier_triplet_shuffled_epochs_1_shard_1_squad2.0_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("roberta_qa_rule_based_hier_triplet_shuffled_epochs_1_shard_1_squad2.0_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_qa_rule_based_hier_triplet_shuffled_epochs_1_shard_1_squad2.0_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|459.7 MB|
+
+## References
+
+https://huggingface.co/AnonymousSub/rule_based_roberta_hier_triplet_shuffled_epochs_1_shard_1_squad2.0
+
+## Included Models
+
+- MultiDocumentAssembler
+- RoBertaForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-roberta_squad_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-09-roberta_squad_finetuned_en.md
new file mode 100644
index 00000000000000..c0aca3509f0841
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-roberta_squad_finetuned_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English roberta_squad_finetuned RoBertaForQuestionAnswering from mylas02
+author: John Snow Labs
+name: roberta_squad_finetuned
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_squad_finetuned` is a English model originally trained by mylas02.
+
+{:.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/roberta_squad_finetuned_en_5.5.0_3.0_1725876364331.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_squad_finetuned_en_5.5.0_3.0_1725876364331.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_squad_finetuned","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_squad_finetuned", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_squad_finetuned|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|461.9 MB|
+
+## References
+
+https://huggingface.co/mylas02/Roberta_SQuaD_FineTuned
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-roberta_vmw_mrqa_s_en.md b/docs/_posts/ahmedlone127/2024-09-09-roberta_vmw_mrqa_s_en.md
new file mode 100644
index 00000000000000..f2abdfd9392715
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-roberta_vmw_mrqa_s_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English roberta_vmw_mrqa_s RoBertaForQuestionAnswering from enriquesaou
+author: John Snow Labs
+name: roberta_vmw_mrqa_s
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_vmw_mrqa_s` is a English model originally trained by enriquesaou.
+
+{:.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/roberta_vmw_mrqa_s_en_5.5.0_3.0_1725876562316.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_vmw_mrqa_s_en_5.5.0_3.0_1725876562316.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_vmw_mrqa_s","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_vmw_mrqa_s", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|roberta_vmw_mrqa_s|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|466.2 MB|
+
+## References
+
+https://huggingface.co/enriquesaou/roberta-vmw-mrqa-s
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-robertalex_bsc_lt_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-09-robertalex_bsc_lt_pipeline_es.md
new file mode 100644
index 00000000000000..c72f438a251118
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-robertalex_bsc_lt_pipeline_es.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Castilian, Spanish robertalex_bsc_lt_pipeline pipeline RoBertaEmbeddings from BSC-LT
+author: John Snow Labs
+name: robertalex_bsc_lt_pipeline
+date: 2024-09-09
+tags: [es, open_source, pipeline, onnx]
+task: Embeddings
+language: es
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`robertalex_bsc_lt_pipeline` is a Castilian, Spanish model originally trained by BSC-LT.
+
+{:.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/robertalex_bsc_lt_pipeline_es_5.5.0_3.0_1725860797781.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/robertalex_bsc_lt_pipeline_es_5.5.0_3.0_1725860797781.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
+
+pipeline = PretrainedPipeline("robertalex_bsc_lt_pipeline", lang = "es")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("robertalex_bsc_lt_pipeline", lang = "es")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|robertalex_bsc_lt_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|es|
+|Size:|298.1 MB|
+
+## References
+
+https://huggingface.co/BSC-LT/RoBERTalex
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-romanian_sentiment_pipeline_ro.md b/docs/_posts/ahmedlone127/2024-09-09-romanian_sentiment_pipeline_ro.md
new file mode 100644
index 00000000000000..d645cc57c416ab
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-romanian_sentiment_pipeline_ro.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Moldavian, Moldovan, Romanian romanian_sentiment_pipeline pipeline BertForSequenceClassification from readerbench
+author: John Snow Labs
+name: romanian_sentiment_pipeline
+date: 2024-09-09
+tags: [ro, open_source, pipeline, onnx]
+task: Text Classification
+language: ro
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`romanian_sentiment_pipeline` is a Moldavian, Moldovan, Romanian model originally trained by readerbench.
+
+{:.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/romanian_sentiment_pipeline_ro_5.5.0_3.0_1725852829372.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/romanian_sentiment_pipeline_ro_5.5.0_3.0_1725852829372.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
+
+pipeline = PretrainedPipeline("romanian_sentiment_pipeline", lang = "ro")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("romanian_sentiment_pipeline", lang = "ro")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|romanian_sentiment_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ro|
+|Size:|431.5 MB|
+
+## References
+
+https://huggingface.co/readerbench/ro-sentiment
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-romanian_sentiment_ro.md b/docs/_posts/ahmedlone127/2024-09-09-romanian_sentiment_ro.md
new file mode 100644
index 00000000000000..37cb0ea42b3640
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-romanian_sentiment_ro.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Moldavian, Moldovan, Romanian romanian_sentiment BertForSequenceClassification from readerbench
+author: John Snow Labs
+name: romanian_sentiment
+date: 2024-09-09
+tags: [ro, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: ro
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`romanian_sentiment` is a Moldavian, Moldovan, Romanian model originally trained by readerbench.
+
+{:.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/romanian_sentiment_ro_5.5.0_3.0_1725852808789.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/romanian_sentiment_ro_5.5.0_3.0_1725852808789.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("romanian_sentiment","ro") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("romanian_sentiment", "ro")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|romanian_sentiment|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|ro|
+|Size:|431.4 MB|
+
+## References
+
+https://huggingface.co/readerbench/ro-sentiment
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-rotten_tomatoes_microsoft_deberta_v3_large_seed_3_en.md b/docs/_posts/ahmedlone127/2024-09-09-rotten_tomatoes_microsoft_deberta_v3_large_seed_3_en.md
new file mode 100644
index 00000000000000..2c30703f9ab4a3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-rotten_tomatoes_microsoft_deberta_v3_large_seed_3_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English rotten_tomatoes_microsoft_deberta_v3_large_seed_3 DeBertaForSequenceClassification from utahnlp
+author: John Snow Labs
+name: rotten_tomatoes_microsoft_deberta_v3_large_seed_3
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rotten_tomatoes_microsoft_deberta_v3_large_seed_3` is a English model originally trained by utahnlp.
+
+{:.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/rotten_tomatoes_microsoft_deberta_v3_large_seed_3_en_5.5.0_3.0_1725849032123.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rotten_tomatoes_microsoft_deberta_v3_large_seed_3_en_5.5.0_3.0_1725849032123.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("rotten_tomatoes_microsoft_deberta_v3_large_seed_3","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("rotten_tomatoes_microsoft_deberta_v3_large_seed_3", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rotten_tomatoes_microsoft_deberta_v3_large_seed_3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/utahnlp/rotten_tomatoes_microsoft_deberta-v3-large_seed-3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-rulebert_v0_1_k4_it.md b/docs/_posts/ahmedlone127/2024-09-09-rulebert_v0_1_k4_it.md
new file mode 100644
index 00000000000000..f494fd8769394f
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-rulebert_v0_1_k4_it.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Italian rulebert_v0_1_k4 XlmRoBertaForSequenceClassification from ribesstefano
+author: John Snow Labs
+name: rulebert_v0_1_k4
+date: 2024-09-09
+tags: [it, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: it
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rulebert_v0_1_k4` is a Italian model originally trained by ribesstefano.
+
+{:.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/rulebert_v0_1_k4_it_5.5.0_3.0_1725871023519.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rulebert_v0_1_k4_it_5.5.0_3.0_1725871023519.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("rulebert_v0_1_k4","it") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("rulebert_v0_1_k4", "it")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rulebert_v0_1_k4|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|it|
+|Size:|812.3 MB|
+
+## References
+
+https://huggingface.co/ribesstefano/RuleBert-v0.1-k4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-rulebert_v0_1_k4_pipeline_it.md b/docs/_posts/ahmedlone127/2024-09-09-rulebert_v0_1_k4_pipeline_it.md
new file mode 100644
index 00000000000000..07fa8333125bf7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-rulebert_v0_1_k4_pipeline_it.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Italian rulebert_v0_1_k4_pipeline pipeline XlmRoBertaForSequenceClassification from ribesstefano
+author: John Snow Labs
+name: rulebert_v0_1_k4_pipeline
+date: 2024-09-09
+tags: [it, open_source, pipeline, onnx]
+task: Text Classification
+language: it
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rulebert_v0_1_k4_pipeline` is a Italian model originally trained by ribesstefano.
+
+{:.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/rulebert_v0_1_k4_pipeline_it_5.5.0_3.0_1725871153793.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rulebert_v0_1_k4_pipeline_it_5.5.0_3.0_1725871153793.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
+
+pipeline = PretrainedPipeline("rulebert_v0_1_k4_pipeline", lang = "it")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rulebert_v0_1_k4_pipeline", lang = "it")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rulebert_v0_1_k4_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|it|
+|Size:|812.3 MB|
+
+## References
+
+https://huggingface.co/ribesstefano/RuleBert-v0.1-k4
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-rulebert_v0_4_k1_pipeline_it.md b/docs/_posts/ahmedlone127/2024-09-09-rulebert_v0_4_k1_pipeline_it.md
new file mode 100644
index 00000000000000..9446a718b4662d
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-rulebert_v0_4_k1_pipeline_it.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Italian rulebert_v0_4_k1_pipeline pipeline XlmRoBertaForSequenceClassification from ribesstefano
+author: John Snow Labs
+name: rulebert_v0_4_k1_pipeline
+date: 2024-09-09
+tags: [it, open_source, pipeline, onnx]
+task: Text Classification
+language: it
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rulebert_v0_4_k1_pipeline` is a Italian model originally trained by ribesstefano.
+
+{:.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/rulebert_v0_4_k1_pipeline_it_5.5.0_3.0_1725870177512.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rulebert_v0_4_k1_pipeline_it_5.5.0_3.0_1725870177512.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
+
+pipeline = PretrainedPipeline("rulebert_v0_4_k1_pipeline", lang = "it")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("rulebert_v0_4_k1_pipeline", lang = "it")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|rulebert_v0_4_k1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|it|
+|Size:|870.5 MB|
+
+## References
+
+https://huggingface.co/ribesstefano/RuleBert-v0.4-k1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-ruroberta_large_pipeline_ru.md b/docs/_posts/ahmedlone127/2024-09-09-ruroberta_large_pipeline_ru.md
new file mode 100644
index 00000000000000..5b98fcc896cf7e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-ruroberta_large_pipeline_ru.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Russian ruroberta_large_pipeline pipeline RoBertaEmbeddings from ai-forever
+author: John Snow Labs
+name: ruroberta_large_pipeline
+date: 2024-09-09
+tags: [ru, open_source, pipeline, onnx]
+task: Embeddings
+language: ru
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ruroberta_large_pipeline` is a Russian model originally trained by ai-forever.
+
+{:.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/ruroberta_large_pipeline_ru_5.5.0_3.0_1725883332553.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ruroberta_large_pipeline_ru_5.5.0_3.0_1725883332553.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
+
+pipeline = PretrainedPipeline("ruroberta_large_pipeline", lang = "ru")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("ruroberta_large_pipeline", lang = "ru")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ruroberta_large_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ru|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/ai-forever/ruRoberta-large
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-ruroberta_large_ru.md b/docs/_posts/ahmedlone127/2024-09-09-ruroberta_large_ru.md
new file mode 100644
index 00000000000000..637b81cfdbf120
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-ruroberta_large_ru.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Russian ruroberta_large RoBertaEmbeddings from ai-forever
+author: John Snow Labs
+name: ruroberta_large
+date: 2024-09-09
+tags: [ru, open_source, onnx, embeddings, roberta]
+task: Embeddings
+language: ru
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ruroberta_large` is a Russian model originally trained by ai-forever.
+
+{:.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/ruroberta_large_ru_5.5.0_3.0_1725883268270.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ruroberta_large_ru_5.5.0_3.0_1725883268270.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = RoBertaEmbeddings.pretrained("ruroberta_large","ru") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = RoBertaEmbeddings.pretrained("ruroberta_large","ru") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|ruroberta_large|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[roberta]|
+|Language:|ru|
+|Size:|1.3 GB|
+
+## References
+
+https://huggingface.co/ai-forever/ruRoberta-large
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-sentence_acceptability_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-sentence_acceptability_pipeline_en.md
new file mode 100644
index 00000000000000..74b3d5f6e22cc8
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-sentence_acceptability_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English sentence_acceptability_pipeline pipeline BertForSequenceClassification from EstherT
+author: John Snow Labs
+name: sentence_acceptability_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentence_acceptability_pipeline` is a English model originally trained by EstherT.
+
+{:.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/sentence_acceptability_pipeline_en_5.5.0_3.0_1725852932315.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentence_acceptability_pipeline_en_5.5.0_3.0_1725852932315.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
+
+pipeline = PretrainedPipeline("sentence_acceptability_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sentence_acceptability_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sentence_acceptability_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/EstherT/sentence-acceptability
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- BertForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-sloberta_finetuned_dlib_1850_1919_pipeline_sl.md b/docs/_posts/ahmedlone127/2024-09-09-sloberta_finetuned_dlib_1850_1919_pipeline_sl.md
new file mode 100644
index 00000000000000..c2b4fa302117fb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-sloberta_finetuned_dlib_1850_1919_pipeline_sl.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Slovenian sloberta_finetuned_dlib_1850_1919_pipeline pipeline CamemBertEmbeddings from janezb
+author: John Snow Labs
+name: sloberta_finetuned_dlib_1850_1919_pipeline
+date: 2024-09-09
+tags: [sl, open_source, pipeline, onnx]
+task: Embeddings
+language: sl
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sloberta_finetuned_dlib_1850_1919_pipeline` is a Slovenian model originally trained by janezb.
+
+{:.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/sloberta_finetuned_dlib_1850_1919_pipeline_sl_5.5.0_3.0_1725851418626.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sloberta_finetuned_dlib_1850_1919_pipeline_sl_5.5.0_3.0_1725851418626.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
+
+pipeline = PretrainedPipeline("sloberta_finetuned_dlib_1850_1919_pipeline", lang = "sl")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sloberta_finetuned_dlib_1850_1919_pipeline", lang = "sl")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sloberta_finetuned_dlib_1850_1919_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|sl|
+|Size:|410.5 MB|
+
+## References
+
+https://huggingface.co/janezb/sloberta-finetuned-dlib-1850-1919
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-sloberta_finetuned_dlib_1850_1919_sl.md b/docs/_posts/ahmedlone127/2024-09-09-sloberta_finetuned_dlib_1850_1919_sl.md
new file mode 100644
index 00000000000000..9409eb5125ac6c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-sloberta_finetuned_dlib_1850_1919_sl.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Slovenian sloberta_finetuned_dlib_1850_1919 CamemBertEmbeddings from janezb
+author: John Snow Labs
+name: sloberta_finetuned_dlib_1850_1919
+date: 2024-09-09
+tags: [sl, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: sl
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sloberta_finetuned_dlib_1850_1919` is a Slovenian model originally trained by janezb.
+
+{:.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/sloberta_finetuned_dlib_1850_1919_sl_5.5.0_3.0_1725851398427.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sloberta_finetuned_dlib_1850_1919_sl_5.5.0_3.0_1725851398427.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("sloberta_finetuned_dlib_1850_1919","sl") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("sloberta_finetuned_dlib_1850_1919","sl") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sloberta_finetuned_dlib_1850_1919|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|sl|
+|Size:|410.5 MB|
+
+## References
+
+https://huggingface.co/janezb/sloberta-finetuned-dlib-1850-1919
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-small_8_c_mr.md b/docs/_posts/ahmedlone127/2024-09-09-small_8_c_mr.md
new file mode 100644
index 00000000000000..1be7ca2ecc3733
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-small_8_c_mr.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Marathi small_8_c WhisperForCTC from simran14
+author: John Snow Labs
+name: small_8_c
+date: 2024-09-09
+tags: [mr, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: mr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`small_8_c` is a Marathi model originally trained by simran14.
+
+{:.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/small_8_c_mr_5.5.0_3.0_1725847862875.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/small_8_c_mr_5.5.0_3.0_1725847862875.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
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("small_8_c","mr") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("small_8_c", "mr")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|small_8_c|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|mr|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/simran14/small_8_c
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-snli_microsoft_deberta_v3_large_seed_2_en.md b/docs/_posts/ahmedlone127/2024-09-09-snli_microsoft_deberta_v3_large_seed_2_en.md
new file mode 100644
index 00000000000000..adcb20ee0200f7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-snli_microsoft_deberta_v3_large_seed_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English snli_microsoft_deberta_v3_large_seed_2 DeBertaForSequenceClassification from utahnlp
+author: John Snow Labs
+name: snli_microsoft_deberta_v3_large_seed_2
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`snli_microsoft_deberta_v3_large_seed_2` is a English model originally trained by utahnlp.
+
+{:.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/snli_microsoft_deberta_v3_large_seed_2_en_5.5.0_3.0_1725849717951.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/snli_microsoft_deberta_v3_large_seed_2_en_5.5.0_3.0_1725849717951.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("snli_microsoft_deberta_v3_large_seed_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("snli_microsoft_deberta_v3_large_seed_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|snli_microsoft_deberta_v3_large_seed_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/utahnlp/snli_microsoft_deberta-v3-large_seed-2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-snli_microsoft_deberta_v3_large_seed_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-snli_microsoft_deberta_v3_large_seed_2_pipeline_en.md
new file mode 100644
index 00000000000000..750cc26a1a0a52
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-snli_microsoft_deberta_v3_large_seed_2_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English snli_microsoft_deberta_v3_large_seed_2_pipeline pipeline DeBertaForSequenceClassification from utahnlp
+author: John Snow Labs
+name: snli_microsoft_deberta_v3_large_seed_2_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`snli_microsoft_deberta_v3_large_seed_2_pipeline` is a English model originally trained by utahnlp.
+
+{:.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/snli_microsoft_deberta_v3_large_seed_2_pipeline_en_5.5.0_3.0_1725849840582.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/snli_microsoft_deberta_v3_large_seed_2_pipeline_en_5.5.0_3.0_1725849840582.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
+
+pipeline = PretrainedPipeline("snli_microsoft_deberta_v3_large_seed_2_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("snli_microsoft_deberta_v3_large_seed_2_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|snli_microsoft_deberta_v3_large_seed_2_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.5 GB|
+
+## References
+
+https://huggingface.co/utahnlp/snli_microsoft_deberta-v3-large_seed-2
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-spanish_catalan_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-spanish_catalan_pipeline_en.md
new file mode 100644
index 00000000000000..031de0a73abcd6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-spanish_catalan_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English spanish_catalan_pipeline pipeline MarianTransformer from Ife
+author: John Snow Labs
+name: spanish_catalan_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spanish_catalan_pipeline` is a English model originally trained by Ife.
+
+{:.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/spanish_catalan_pipeline_en_5.5.0_3.0_1725863304218.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spanish_catalan_pipeline_en_5.5.0_3.0_1725863304218.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
+
+pipeline = PretrainedPipeline("spanish_catalan_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("spanish_catalan_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|spanish_catalan_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|466.7 MB|
+
+## References
+
+https://huggingface.co/Ife/ES-CA
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-squad_qa_model_horyekhunley_en.md b/docs/_posts/ahmedlone127/2024-09-09-squad_qa_model_horyekhunley_en.md
new file mode 100644
index 00000000000000..324539f0dee0e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-squad_qa_model_horyekhunley_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English squad_qa_model_horyekhunley DistilBertForQuestionAnswering from horyekhunley
+author: John Snow Labs
+name: squad_qa_model_horyekhunley
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`squad_qa_model_horyekhunley` is a English model originally trained by horyekhunley.
+
+{:.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/squad_qa_model_horyekhunley_en_5.5.0_3.0_1725876966751.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/squad_qa_model_horyekhunley_en_5.5.0_3.0_1725876966751.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("squad_qa_model_horyekhunley","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("squad_qa_model_horyekhunley", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|squad_qa_model_horyekhunley|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/horyekhunley/squad_qa_model
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-sroberta_f_pipeline_hr.md b/docs/_posts/ahmedlone127/2024-09-09-sroberta_f_pipeline_hr.md
new file mode 100644
index 00000000000000..ab8749e3d272de
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-sroberta_f_pipeline_hr.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: Croatian sroberta_f_pipeline pipeline RoBertaEmbeddings from Andrija
+author: John Snow Labs
+name: sroberta_f_pipeline
+date: 2024-09-09
+tags: [hr, open_source, pipeline, onnx]
+task: Embeddings
+language: hr
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sroberta_f_pipeline` is a Croatian model originally trained by Andrija.
+
+{:.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/sroberta_f_pipeline_hr_5.5.0_3.0_1725883896336.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sroberta_f_pipeline_hr_5.5.0_3.0_1725883896336.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
+
+pipeline = PretrainedPipeline("sroberta_f_pipeline", lang = "hr")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("sroberta_f_pipeline", lang = "hr")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|sroberta_f_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|hr|
+|Size:|300.3 MB|
+
+## References
+
+https://huggingface.co/Andrija/SRoBERTa-F
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- RoBertaEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-stt_huggin_face_tech_nepal_bhasa_data_en.md b/docs/_posts/ahmedlone127/2024-09-09-stt_huggin_face_tech_nepal_bhasa_data_en.md
new file mode 100644
index 00000000000000..8a44357e6d4f97
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-stt_huggin_face_tech_nepal_bhasa_data_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English stt_huggin_face_tech_nepal_bhasa_data DistilBertForQuestionAnswering from Jose-Ribeir
+author: John Snow Labs
+name: stt_huggin_face_tech_nepal_bhasa_data
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, distilbert]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DistilBertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`stt_huggin_face_tech_nepal_bhasa_data` is a English model originally trained by Jose-Ribeir.
+
+{:.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/stt_huggin_face_tech_nepal_bhasa_data_en_5.5.0_3.0_1725869148579.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/stt_huggin_face_tech_nepal_bhasa_data_en_5.5.0_3.0_1725869148579.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = DistilBertForQuestionAnswering.pretrained("stt_huggin_face_tech_nepal_bhasa_data","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = DistilBertForQuestionAnswering.pretrained("stt_huggin_face_tech_nepal_bhasa_data", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|stt_huggin_face_tech_nepal_bhasa_data|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Jose-Ribeir/stt_Huggin_face_tech_new_data
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-stt_huggin_face_tech_nepal_bhasa_data_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-stt_huggin_face_tech_nepal_bhasa_data_pipeline_en.md
new file mode 100644
index 00000000000000..178abb0237e277
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-stt_huggin_face_tech_nepal_bhasa_data_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English stt_huggin_face_tech_nepal_bhasa_data_pipeline pipeline DistilBertForQuestionAnswering from Jose-Ribeir
+author: John Snow Labs
+name: stt_huggin_face_tech_nepal_bhasa_data_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`stt_huggin_face_tech_nepal_bhasa_data_pipeline` is a English model originally trained by Jose-Ribeir.
+
+{:.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/stt_huggin_face_tech_nepal_bhasa_data_pipeline_en_5.5.0_3.0_1725869160674.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/stt_huggin_face_tech_nepal_bhasa_data_pipeline_en_5.5.0_3.0_1725869160674.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
+
+pipeline = PretrainedPipeline("stt_huggin_face_tech_nepal_bhasa_data_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("stt_huggin_face_tech_nepal_bhasa_data_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|stt_huggin_face_tech_nepal_bhasa_data_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|247.2 MB|
+
+## References
+
+https://huggingface.co/Jose-Ribeir/stt_Huggin_face_tech_new_data
+
+## Included Models
+
+- MultiDocumentAssembler
+- DistilBertForQuestionAnswering
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-tmp_trainer_juncodh_en.md b/docs/_posts/ahmedlone127/2024-09-09-tmp_trainer_juncodh_en.md
new file mode 100644
index 00000000000000..ca87aedf81a55e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-tmp_trainer_juncodh_en.md
@@ -0,0 +1,86 @@
+---
+layout: model
+title: English tmp_trainer_juncodh RoBertaForQuestionAnswering from Juncodh
+author: John Snow Labs
+name: tmp_trainer_juncodh
+date: 2024-09-09
+tags: [en, open_source, onnx, question_answering, roberta]
+task: Question Answering
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: RoBertaForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tmp_trainer_juncodh` is a English model originally trained by Juncodh.
+
+{:.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/tmp_trainer_juncodh_en_5.5.0_3.0_1725876560402.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tmp_trainer_juncodh_en_5.5.0_3.0_1725876560402.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
+             
+documentAssembler = MultiDocumentAssembler() \
+     .setInputCol(["question", "context"]) \
+     .setOutputCol(["document_question", "document_context"])
+    
+spanClassifier = RoBertaForQuestionAnswering.pretrained("tmp_trainer_juncodh","en") \
+     .setInputCols(["document_question","document_context"]) \
+     .setOutputCol("answer")
+
+pipeline = Pipeline().setStages([documentAssembler, spanClassifier])
+data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new MultiDocumentAssembler()
+    .setInputCol(Array("question", "context")) 
+    .setOutputCol(Array("document_question", "document_context"))
+    
+val spanClassifier = RoBertaForQuestionAnswering.pretrained("tmp_trainer_juncodh", "en")
+    .setInputCols(Array("document_question","document_context")) 
+    .setOutputCol("answer") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|tmp_trainer_juncodh|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|306.2 MB|
+
+## References
+
+https://huggingface.co/Juncodh/tmp_trainer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-translate_model_error_v0_4_mitrashatru_en.md b/docs/_posts/ahmedlone127/2024-09-09-translate_model_error_v0_4_mitrashatru_en.md
new file mode 100644
index 00000000000000..c067a1e497d0d9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-translate_model_error_v0_4_mitrashatru_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English translate_model_error_v0_4_mitrashatru MarianTransformer from mitrashatru
+author: John Snow Labs
+name: translate_model_error_v0_4_mitrashatru
+date: 2024-09-09
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`translate_model_error_v0_4_mitrashatru` is a English model originally trained by mitrashatru.
+
+{:.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/translate_model_error_v0_4_mitrashatru_en_5.5.0_3.0_1725863233776.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/translate_model_error_v0_4_mitrashatru_en_5.5.0_3.0_1725863233776.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("translate_model_error_v0_4_mitrashatru","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("translate_model_error_v0_4_mitrashatru","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|translate_model_error_v0_4_mitrashatru|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|523.2 MB|
+
+## References
+
+https://huggingface.co/mitrashatru/translate_model_error_v0.4
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-usingweb_en.md b/docs/_posts/ahmedlone127/2024-09-09-usingweb_en.md
new file mode 100644
index 00000000000000..7d65f7221277ce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-usingweb_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English usingweb CamemBertEmbeddings from thucdangvan020999
+author: John Snow Labs
+name: usingweb
+date: 2024-09-09
+tags: [en, open_source, onnx, embeddings, camembert]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertEmbeddings
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`usingweb` is a English model originally trained by thucdangvan020999.
+
+{:.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/usingweb_en_5.5.0_3.0_1725851917416.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/usingweb_en_5.5.0_3.0_1725851917416.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+    
+tokenizer = Tokenizer() \ 
+      .setInputCols("document") \ 
+      .setOutputCol("token")
+
+embeddings = CamemBertEmbeddings.pretrained("usingweb","en") \
+      .setInputCols(["document", "token"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+    
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val embeddings = CamemBertEmbeddings.pretrained("usingweb","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("embeddings")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|usingweb|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[camembert]|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/thucdangvan020999/usingweb
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-usingweb_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-usingweb_pipeline_en.md
new file mode 100644
index 00000000000000..603bc3df7aa87a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-usingweb_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English usingweb_pipeline pipeline CamemBertEmbeddings from thucdangvan020999
+author: John Snow Labs
+name: usingweb_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Embeddings
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`usingweb_pipeline` is a English model originally trained by thucdangvan020999.
+
+{:.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/usingweb_pipeline_en_5.5.0_3.0_1725851994368.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/usingweb_pipeline_en_5.5.0_3.0_1725851994368.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
+
+pipeline = PretrainedPipeline("usingweb_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("usingweb_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|usingweb_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|264.0 MB|
+
+## References
+
+https://huggingface.co/thucdangvan020999/usingweb
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- CamemBertEmbeddings
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-vn_japanese_english_helsinki_en.md b/docs/_posts/ahmedlone127/2024-09-09-vn_japanese_english_helsinki_en.md
new file mode 100644
index 00000000000000..5e7b8a7b7d9c86
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-vn_japanese_english_helsinki_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English vn_japanese_english_helsinki MarianTransformer from twieland
+author: John Snow Labs
+name: vn_japanese_english_helsinki
+date: 2024-09-09
+tags: [en, open_source, onnx, translation, marian]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: MarianTransformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vn_japanese_english_helsinki` is a English model originally trained by twieland.
+
+{:.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/vn_japanese_english_helsinki_en_5.5.0_3.0_1725840067770.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vn_japanese_english_helsinki_en_5.5.0_3.0_1725840067770.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
+ 
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \
+      .setInputCols(["document"]) \
+      .setOutputCol("translation")
+
+marian = MarianTransformer.pretrained("vn_japanese_english_helsinki","en") \
+      .setInputCols(["sentence"]) \
+      .setOutputCol("embeddings")       
+        
+pipeline = Pipeline().setStages([documentAssembler, sentenceDL, marian])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler() 
+    .setInputCol("text") 
+    .setOutputCol("document")
+
+val marian = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+	.setInputCols(Array("document"))
+	.setOutputCol("sentence")
+
+val embeddings = MarianTransformer.pretrained("vn_japanese_english_helsinki","en") 
+    .setInputCols(Array("sentence")) 
+    .setOutputCol("translation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, marian))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vn_japanese_english_helsinki|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[sentences]|
+|Output Labels:|[translation]|
+|Language:|en|
+|Size:|516.1 MB|
+
+## References
+
+https://huggingface.co/twieland/VN_ja-en_helsinki
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-vn_japanese_english_helsinki_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-vn_japanese_english_helsinki_pipeline_en.md
new file mode 100644
index 00000000000000..98eaa01063aa42
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-vn_japanese_english_helsinki_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English vn_japanese_english_helsinki_pipeline pipeline MarianTransformer from twieland
+author: John Snow Labs
+name: vn_japanese_english_helsinki_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Translation
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained MarianTransformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vn_japanese_english_helsinki_pipeline` is a English model originally trained by twieland.
+
+{:.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/vn_japanese_english_helsinki_pipeline_en_5.5.0_3.0_1725840095908.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vn_japanese_english_helsinki_pipeline_en_5.5.0_3.0_1725840095908.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
+
+pipeline = PretrainedPipeline("vn_japanese_english_helsinki_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("vn_japanese_english_helsinki_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|vn_japanese_english_helsinki_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|516.6 MB|
+
+## References
+
+https://huggingface.co/twieland/VN_ja-en_helsinki
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- MarianTransformer
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-w266_model4_bert_automodelforsequenceclassification_en.md b/docs/_posts/ahmedlone127/2024-09-09-w266_model4_bert_automodelforsequenceclassification_en.md
new file mode 100644
index 00000000000000..6d0949bb3ee8f3
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-w266_model4_bert_automodelforsequenceclassification_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English w266_model4_bert_automodelforsequenceclassification BertForSequenceClassification from arindamatcalgm
+author: John Snow Labs
+name: w266_model4_bert_automodelforsequenceclassification
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, bert]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`w266_model4_bert_automodelforsequenceclassification` is a English model originally trained by arindamatcalgm.
+
+{:.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/w266_model4_bert_automodelforsequenceclassification_en_5.5.0_3.0_1725856790963.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/w266_model4_bert_automodelforsequenceclassification_en_5.5.0_3.0_1725856790963.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = BertForSequenceClassification.pretrained("w266_model4_bert_automodelforsequenceclassification","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = BertForSequenceClassification.pretrained("w266_model4_bert_automodelforsequenceclassification", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|w266_model4_bert_automodelforsequenceclassification|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|409.4 MB|
+
+## References
+
+https://huggingface.co/arindamatcalgm/w266_model4_BERT_AutoModelForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-whispasr_hi.md b/docs/_posts/ahmedlone127/2024-09-09-whispasr_hi.md
new file mode 100644
index 00000000000000..498894c89a2e95
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-whispasr_hi.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Hindi whispasr WhisperForCTC from Rithik101
+author: John Snow Labs
+name: whispasr
+date: 2024-09-09
+tags: [hi, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: hi
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whispasr` is a Hindi model originally trained by Rithik101.
+
+{:.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/whispasr_hi_5.5.0_3.0_1725844863302.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whispasr_hi_5.5.0_3.0_1725844863302.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
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whispasr","hi") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whispasr", "hi")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whispasr|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|hi|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/Rithik101/WhispASR
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-whisper_base_dutch_3_en.md b/docs/_posts/ahmedlone127/2024-09-09-whisper_base_dutch_3_en.md
new file mode 100644
index 00000000000000..0f5398f2289b86
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-whisper_base_dutch_3_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English whisper_base_dutch_3 WhisperForCTC from SuperKogito
+author: John Snow Labs
+name: whisper_base_dutch_3
+date: 2024-09-09
+tags: [en, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_base_dutch_3` is a English model originally trained by SuperKogito.
+
+{:.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/whisper_base_dutch_3_en_5.5.0_3.0_1725841449647.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_base_dutch_3_en_5.5.0_3.0_1725841449647.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
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_base_dutch_3","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_base_dutch_3", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_base_dutch_3|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|398.5 MB|
+
+## References
+
+https://huggingface.co/SuperKogito/whisper-base-nl-3
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-whisper_base_dutch_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-whisper_base_dutch_3_pipeline_en.md
new file mode 100644
index 00000000000000..56ba011ab6fa05
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-whisper_base_dutch_3_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English whisper_base_dutch_3_pipeline pipeline WhisperForCTC from SuperKogito
+author: John Snow Labs
+name: whisper_base_dutch_3_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_base_dutch_3_pipeline` is a English model originally trained by SuperKogito.
+
+{:.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/whisper_base_dutch_3_pipeline_en_5.5.0_3.0_1725841557626.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_base_dutch_3_pipeline_en_5.5.0_3.0_1725841557626.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
+
+pipeline = PretrainedPipeline("whisper_base_dutch_3_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_base_dutch_3_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_base_dutch_3_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|398.6 MB|
+
+## References
+
+https://huggingface.co/SuperKogito/whisper-base-nl-3
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-whisper_base_japanese_ja.md b/docs/_posts/ahmedlone127/2024-09-09-whisper_base_japanese_ja.md
new file mode 100644
index 00000000000000..2dd79c1675b302
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-whisper_base_japanese_ja.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Japanese whisper_base_japanese WhisperForCTC from Ivydata
+author: John Snow Labs
+name: whisper_base_japanese
+date: 2024-09-09
+tags: [ja, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_base_japanese` is a Japanese model originally trained by Ivydata.
+
+{:.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/whisper_base_japanese_ja_5.5.0_3.0_1725844374788.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_base_japanese_ja_5.5.0_3.0_1725844374788.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
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_base_japanese","ja") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_base_japanese", "ja")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_base_japanese|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|ja|
+|Size:|642.2 MB|
+
+## References
+
+https://huggingface.co/Ivydata/whisper-base-japanese
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-whisper_base_japanese_pipeline_ja.md b/docs/_posts/ahmedlone127/2024-09-09-whisper_base_japanese_pipeline_ja.md
new file mode 100644
index 00000000000000..b19352356b9cce
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-whisper_base_japanese_pipeline_ja.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Japanese whisper_base_japanese_pipeline pipeline WhisperForCTC from Ivydata
+author: John Snow Labs
+name: whisper_base_japanese_pipeline
+date: 2024-09-09
+tags: [ja, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: ja
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_base_japanese_pipeline` is a Japanese model originally trained by Ivydata.
+
+{:.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/whisper_base_japanese_pipeline_ja_5.5.0_3.0_1725844409920.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_base_japanese_pipeline_ja_5.5.0_3.0_1725844409920.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
+
+pipeline = PretrainedPipeline("whisper_base_japanese_pipeline", lang = "ja")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_base_japanese_pipeline", lang = "ja")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_base_japanese_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ja|
+|Size:|642.2 MB|
+
+## References
+
+https://huggingface.co/Ivydata/whisper-base-japanese
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-whisper_base_lithuanian_lt.md b/docs/_posts/ahmedlone127/2024-09-09-whisper_base_lithuanian_lt.md
new file mode 100644
index 00000000000000..4605bba01d85cb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-whisper_base_lithuanian_lt.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Lithuanian whisper_base_lithuanian WhisperForCTC from Aismantas
+author: John Snow Labs
+name: whisper_base_lithuanian
+date: 2024-09-09
+tags: [lt, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: lt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_base_lithuanian` is a Lithuanian model originally trained by Aismantas.
+
+{:.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/whisper_base_lithuanian_lt_5.5.0_3.0_1725846185532.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_base_lithuanian_lt_5.5.0_3.0_1725846185532.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
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_base_lithuanian","lt") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_base_lithuanian", "lt")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_base_lithuanian|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|lt|
+|Size:|642.0 MB|
+
+## References
+
+https://huggingface.co/Aismantas/whisper-base-lithuanian
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-whisper_base_thai_pipeline_th.md b/docs/_posts/ahmedlone127/2024-09-09-whisper_base_thai_pipeline_th.md
new file mode 100644
index 00000000000000..bbf79861dc1dfe
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-whisper_base_thai_pipeline_th.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Thai whisper_base_thai_pipeline pipeline WhisperForCTC from juierror
+author: John Snow Labs
+name: whisper_base_thai_pipeline
+date: 2024-09-09
+tags: [th, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: th
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_base_thai_pipeline` is a Thai model originally trained by juierror.
+
+{:.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/whisper_base_thai_pipeline_th_5.5.0_3.0_1725843023477.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_base_thai_pipeline_th_5.5.0_3.0_1725843023477.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
+
+pipeline = PretrainedPipeline("whisper_base_thai_pipeline", lang = "th")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_base_thai_pipeline", lang = "th")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_base_thai_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|th|
+|Size:|642.6 MB|
+
+## References
+
+https://huggingface.co/juierror/whisper-base-thai
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-whisper_base_thai_th.md b/docs/_posts/ahmedlone127/2024-09-09-whisper_base_thai_th.md
new file mode 100644
index 00000000000000..d0962eb24605ac
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-whisper_base_thai_th.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Thai whisper_base_thai WhisperForCTC from juierror
+author: John Snow Labs
+name: whisper_base_thai
+date: 2024-09-09
+tags: [th, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: th
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_base_thai` is a Thai model originally trained by juierror.
+
+{:.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/whisper_base_thai_th_5.5.0_3.0_1725842991107.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_base_thai_th_5.5.0_3.0_1725842991107.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
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_base_thai","th") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_base_thai", "th")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_base_thai|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|th|
+|Size:|642.6 MB|
+
+## References
+
+https://huggingface.co/juierror/whisper-base-thai
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-whisper_small_chinese_twi_jingmiao_pipeline_zh.md b/docs/_posts/ahmedlone127/2024-09-09-whisper_small_chinese_twi_jingmiao_pipeline_zh.md
new file mode 100644
index 00000000000000..3f745035496447
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-whisper_small_chinese_twi_jingmiao_pipeline_zh.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Chinese whisper_small_chinese_twi_jingmiao_pipeline pipeline WhisperForCTC from Jingmiao
+author: John Snow Labs
+name: whisper_small_chinese_twi_jingmiao_pipeline
+date: 2024-09-09
+tags: [zh, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: zh
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_chinese_twi_jingmiao_pipeline` is a Chinese model originally trained by Jingmiao.
+
+{:.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/whisper_small_chinese_twi_jingmiao_pipeline_zh_5.5.0_3.0_1725844660592.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_chinese_twi_jingmiao_pipeline_zh_5.5.0_3.0_1725844660592.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
+
+pipeline = PretrainedPipeline("whisper_small_chinese_twi_jingmiao_pipeline", lang = "zh")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_small_chinese_twi_jingmiao_pipeline", lang = "zh")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_chinese_twi_jingmiao_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|zh|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/Jingmiao/whisper-small-zh_tw
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-whisper_small_chinese_twi_jingmiao_zh.md b/docs/_posts/ahmedlone127/2024-09-09-whisper_small_chinese_twi_jingmiao_zh.md
new file mode 100644
index 00000000000000..c41e6ae6a1d863
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-whisper_small_chinese_twi_jingmiao_zh.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Chinese whisper_small_chinese_twi_jingmiao WhisperForCTC from Jingmiao
+author: John Snow Labs
+name: whisper_small_chinese_twi_jingmiao
+date: 2024-09-09
+tags: [zh, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: zh
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_chinese_twi_jingmiao` is a Chinese model originally trained by Jingmiao.
+
+{:.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/whisper_small_chinese_twi_jingmiao_zh_5.5.0_3.0_1725844576330.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_chinese_twi_jingmiao_zh_5.5.0_3.0_1725844576330.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
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_small_chinese_twi_jingmiao","zh") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_small_chinese_twi_jingmiao", "zh")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_chinese_twi_jingmiao|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|zh|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/Jingmiao/whisper-small-zh_tw
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-whisper_small_finetuned_hindi_hi.md b/docs/_posts/ahmedlone127/2024-09-09-whisper_small_finetuned_hindi_hi.md
new file mode 100644
index 00000000000000..c2e2e35344ed06
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-whisper_small_finetuned_hindi_hi.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Hindi whisper_small_finetuned_hindi WhisperForCTC from yash072
+author: John Snow Labs
+name: whisper_small_finetuned_hindi
+date: 2024-09-09
+tags: [hi, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: hi
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_finetuned_hindi` is a Hindi model originally trained by yash072.
+
+{:.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/whisper_small_finetuned_hindi_hi_5.5.0_3.0_1725843879247.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_finetuned_hindi_hi_5.5.0_3.0_1725843879247.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
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_small_finetuned_hindi","hi") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_small_finetuned_hindi", "hi")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_finetuned_hindi|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|hi|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/yash072/Whisper-small-finetuned-hindi
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-whisper_small_finetuned_hindi_pipeline_hi.md b/docs/_posts/ahmedlone127/2024-09-09-whisper_small_finetuned_hindi_pipeline_hi.md
new file mode 100644
index 00000000000000..ae2365a0015af7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-whisper_small_finetuned_hindi_pipeline_hi.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Hindi whisper_small_finetuned_hindi_pipeline pipeline WhisperForCTC from yash072
+author: John Snow Labs
+name: whisper_small_finetuned_hindi_pipeline
+date: 2024-09-09
+tags: [hi, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: hi
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_finetuned_hindi_pipeline` is a Hindi model originally trained by yash072.
+
+{:.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/whisper_small_finetuned_hindi_pipeline_hi_5.5.0_3.0_1725843961077.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_finetuned_hindi_pipeline_hi_5.5.0_3.0_1725843961077.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
+
+pipeline = PretrainedPipeline("whisper_small_finetuned_hindi_pipeline", lang = "hi")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_small_finetuned_hindi_pipeline", lang = "hi")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_finetuned_hindi_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|hi|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/yash072/Whisper-small-finetuned-hindi
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-whisper_small_hausa_hi.md b/docs/_posts/ahmedlone127/2024-09-09-whisper_small_hausa_hi.md
new file mode 100644
index 00000000000000..80a70e46fe30ba
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-whisper_small_hausa_hi.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Hindi whisper_small_hausa WhisperForCTC from bimamuhammad
+author: John Snow Labs
+name: whisper_small_hausa
+date: 2024-09-09
+tags: [hi, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: hi
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_hausa` is a Hindi model originally trained by bimamuhammad.
+
+{:.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/whisper_small_hausa_hi_5.5.0_3.0_1725845882036.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_hausa_hi_5.5.0_3.0_1725845882036.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
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_small_hausa","hi") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_small_hausa", "hi")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_hausa|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|hi|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/bimamuhammad/whisper-small-ha
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-whisper_small_hausa_pipeline_hi.md b/docs/_posts/ahmedlone127/2024-09-09-whisper_small_hausa_pipeline_hi.md
new file mode 100644
index 00000000000000..adbd9e1d20b5f6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-whisper_small_hausa_pipeline_hi.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Hindi whisper_small_hausa_pipeline pipeline WhisperForCTC from bimamuhammad
+author: John Snow Labs
+name: whisper_small_hausa_pipeline
+date: 2024-09-09
+tags: [hi, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: hi
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_hausa_pipeline` is a Hindi model originally trained by bimamuhammad.
+
+{:.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/whisper_small_hausa_pipeline_hi_5.5.0_3.0_1725846196138.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_hausa_pipeline_hi_5.5.0_3.0_1725846196138.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
+
+pipeline = PretrainedPipeline("whisper_small_hausa_pipeline", lang = "hi")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_small_hausa_pipeline", lang = "hi")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_hausa_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|hi|
+|Size:|1.1 GB|
+
+## References
+
+https://huggingface.co/bimamuhammad/whisper-small-ha
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-whisper_small_nepali_subu19_ne.md b/docs/_posts/ahmedlone127/2024-09-09-whisper_small_nepali_subu19_ne.md
new file mode 100644
index 00000000000000..b69f2d43f5dc45
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-whisper_small_nepali_subu19_ne.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Nepali (macrolanguage) whisper_small_nepali_subu19 WhisperForCTC from Subu19
+author: John Snow Labs
+name: whisper_small_nepali_subu19
+date: 2024-09-09
+tags: [ne, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: ne
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_nepali_subu19` is a Nepali (macrolanguage) model originally trained by Subu19.
+
+{:.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/whisper_small_nepali_subu19_ne_5.5.0_3.0_1725841786076.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_nepali_subu19_ne_5.5.0_3.0_1725841786076.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
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_small_nepali_subu19","ne") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_small_nepali_subu19", "ne")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_nepali_subu19|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|ne|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/Subu19/whisper-small-nepali
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-whisper_small_nepali_subu19_pipeline_ne.md b/docs/_posts/ahmedlone127/2024-09-09-whisper_small_nepali_subu19_pipeline_ne.md
new file mode 100644
index 00000000000000..14515871dbb8ee
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-whisper_small_nepali_subu19_pipeline_ne.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Nepali (macrolanguage) whisper_small_nepali_subu19_pipeline pipeline WhisperForCTC from Subu19
+author: John Snow Labs
+name: whisper_small_nepali_subu19_pipeline
+date: 2024-09-09
+tags: [ne, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: ne
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_nepali_subu19_pipeline` is a Nepali (macrolanguage) model originally trained by Subu19.
+
+{:.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/whisper_small_nepali_subu19_pipeline_ne_5.5.0_3.0_1725841891354.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_nepali_subu19_pipeline_ne_5.5.0_3.0_1725841891354.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
+
+pipeline = PretrainedPipeline("whisper_small_nepali_subu19_pipeline", lang = "ne")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_small_nepali_subu19_pipeline", lang = "ne")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_nepali_subu19_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ne|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/Subu19/whisper-small-nepali
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-whisper_small_portuguese_my_north_ai_pipeline_pt.md b/docs/_posts/ahmedlone127/2024-09-09-whisper_small_portuguese_my_north_ai_pipeline_pt.md
new file mode 100644
index 00000000000000..221c9eb5c06e78
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-whisper_small_portuguese_my_north_ai_pipeline_pt.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Portuguese whisper_small_portuguese_my_north_ai_pipeline pipeline WhisperForCTC from my-north-ai
+author: John Snow Labs
+name: whisper_small_portuguese_my_north_ai_pipeline
+date: 2024-09-09
+tags: [pt, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: pt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_portuguese_my_north_ai_pipeline` is a Portuguese model originally trained by my-north-ai.
+
+{:.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/whisper_small_portuguese_my_north_ai_pipeline_pt_5.5.0_3.0_1725847107782.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_portuguese_my_north_ai_pipeline_pt_5.5.0_3.0_1725847107782.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
+
+pipeline = PretrainedPipeline("whisper_small_portuguese_my_north_ai_pipeline", lang = "pt")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_small_portuguese_my_north_ai_pipeline", lang = "pt")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_portuguese_my_north_ai_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|pt|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/my-north-ai/whisper-small-pt
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-whisper_small_portuguese_my_north_ai_pt.md b/docs/_posts/ahmedlone127/2024-09-09-whisper_small_portuguese_my_north_ai_pt.md
new file mode 100644
index 00000000000000..51ddfa199d099a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-whisper_small_portuguese_my_north_ai_pt.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Portuguese whisper_small_portuguese_my_north_ai WhisperForCTC from my-north-ai
+author: John Snow Labs
+name: whisper_small_portuguese_my_north_ai
+date: 2024-09-09
+tags: [pt, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: pt
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_portuguese_my_north_ai` is a Portuguese model originally trained by my-north-ai.
+
+{:.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/whisper_small_portuguese_my_north_ai_pt_5.5.0_3.0_1725847024995.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_portuguese_my_north_ai_pt_5.5.0_3.0_1725847024995.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
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_small_portuguese_my_north_ai","pt") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_small_portuguese_my_north_ai", "pt")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_portuguese_my_north_ai|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|pt|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/my-north-ai/whisper-small-pt
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-whisper_small_russian_erlandekh_ru.md b/docs/_posts/ahmedlone127/2024-09-09-whisper_small_russian_erlandekh_ru.md
new file mode 100644
index 00000000000000..a4d6824cb7e2e6
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-whisper_small_russian_erlandekh_ru.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Russian whisper_small_russian_erlandekh WhisperForCTC from erlandekh
+author: John Snow Labs
+name: whisper_small_russian_erlandekh
+date: 2024-09-09
+tags: [ru, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: ru
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_small_russian_erlandekh` is a Russian model originally trained by erlandekh.
+
+{:.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/whisper_small_russian_erlandekh_ru_5.5.0_3.0_1725845931008.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_russian_erlandekh_ru_5.5.0_3.0_1725845931008.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
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_small_russian_erlandekh","ru") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_small_russian_erlandekh", "ru")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_small_russian_erlandekh|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|ru|
+|Size:|1.7 GB|
+
+## References
+
+https://huggingface.co/erlandekh/whisper-small-russian
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-whisper_test_tiny_dcjack_en.md b/docs/_posts/ahmedlone127/2024-09-09-whisper_test_tiny_dcjack_en.md
new file mode 100644
index 00000000000000..fd156bcb9f9e87
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-whisper_test_tiny_dcjack_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English whisper_test_tiny_dcjack WhisperForCTC from dcjack
+author: John Snow Labs
+name: whisper_test_tiny_dcjack
+date: 2024-09-09
+tags: [en, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_test_tiny_dcjack` is a English model originally trained by dcjack.
+
+{:.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/whisper_test_tiny_dcjack_en_5.5.0_3.0_1725847155610.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_test_tiny_dcjack_en_5.5.0_3.0_1725847155610.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
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_test_tiny_dcjack","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_test_tiny_dcjack", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_test_tiny_dcjack|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|242.8 MB|
+
+## References
+
+https://huggingface.co/dcjack/whisper-test-tiny
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-whisper_test_tiny_dcjack_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-whisper_test_tiny_dcjack_pipeline_en.md
new file mode 100644
index 00000000000000..4ba5b4d7a85d0b
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-whisper_test_tiny_dcjack_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English whisper_test_tiny_dcjack_pipeline pipeline WhisperForCTC from dcjack
+author: John Snow Labs
+name: whisper_test_tiny_dcjack_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_test_tiny_dcjack_pipeline` is a English model originally trained by dcjack.
+
+{:.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/whisper_test_tiny_dcjack_pipeline_en_5.5.0_3.0_1725847223101.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_test_tiny_dcjack_pipeline_en_5.5.0_3.0_1725847223101.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
+
+pipeline = PretrainedPipeline("whisper_test_tiny_dcjack_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_test_tiny_dcjack_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_test_tiny_dcjack_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|242.9 MB|
+
+## References
+
+https://huggingface.co/dcjack/whisper-test-tiny
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-whisper_tiny_ak_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-whisper_tiny_ak_pipeline_en.md
new file mode 100644
index 00000000000000..83219042c338bc
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-whisper_tiny_ak_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English whisper_tiny_ak_pipeline pipeline WhisperForCTC from nyarkssss
+author: John Snow Labs
+name: whisper_tiny_ak_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_tiny_ak_pipeline` is a English model originally trained by nyarkssss.
+
+{:.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/whisper_tiny_ak_pipeline_en_5.5.0_3.0_1725846235544.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_ak_pipeline_en_5.5.0_3.0_1725846235544.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
+
+pipeline = PretrainedPipeline("whisper_tiny_ak_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_tiny_ak_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_tiny_ak_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|390.0 MB|
+
+## References
+
+https://huggingface.co/nyarkssss/whisper-tiny-ak
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-whisper_tiny_dutch_nl.md b/docs/_posts/ahmedlone127/2024-09-09-whisper_tiny_dutch_nl.md
new file mode 100644
index 00000000000000..4a1590c6ec886a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-whisper_tiny_dutch_nl.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Dutch, Flemish whisper_tiny_dutch WhisperForCTC from renesteeman
+author: John Snow Labs
+name: whisper_tiny_dutch
+date: 2024-09-09
+tags: [nl, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: nl
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_tiny_dutch` is a Dutch, Flemish model originally trained by renesteeman.
+
+{:.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/whisper_tiny_dutch_nl_5.5.0_3.0_1725842213467.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_dutch_nl_5.5.0_3.0_1725842213467.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
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_tiny_dutch","nl") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_tiny_dutch", "nl")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_tiny_dutch|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|nl|
+|Size:|390.8 MB|
+
+## References
+
+https://huggingface.co/renesteeman/whisper-tiny-dutch
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-whisper_tiny_mizogeneral_en.md b/docs/_posts/ahmedlone127/2024-09-09-whisper_tiny_mizogeneral_en.md
new file mode 100644
index 00000000000000..a6cc65ec2cf189
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-whisper_tiny_mizogeneral_en.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: English whisper_tiny_mizogeneral WhisperForCTC from AnalyticalRecon
+author: John Snow Labs
+name: whisper_tiny_mizogeneral
+date: 2024-09-09
+tags: [en, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_tiny_mizogeneral` is a English model originally trained by AnalyticalRecon.
+
+{:.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/whisper_tiny_mizogeneral_en_5.5.0_3.0_1725844565117.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_mizogeneral_en_5.5.0_3.0_1725844565117.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
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_tiny_mizogeneral","en") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_tiny_mizogeneral", "en")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_tiny_mizogeneral|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|en|
+|Size:|390.0 MB|
+
+## References
+
+https://huggingface.co/AnalyticalRecon/whisper-tiny-mizoGeneral
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-whisper_tiny_mizogeneral_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-whisper_tiny_mizogeneral_pipeline_en.md
new file mode 100644
index 00000000000000..c18133263ab216
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-whisper_tiny_mizogeneral_pipeline_en.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: English whisper_tiny_mizogeneral_pipeline pipeline WhisperForCTC from AnalyticalRecon
+author: John Snow Labs
+name: whisper_tiny_mizogeneral_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_tiny_mizogeneral_pipeline` is a English model originally trained by AnalyticalRecon.
+
+{:.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/whisper_tiny_mizogeneral_pipeline_en_5.5.0_3.0_1725844587040.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_mizogeneral_pipeline_en_5.5.0_3.0_1725844587040.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
+
+pipeline = PretrainedPipeline("whisper_tiny_mizogeneral_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_tiny_mizogeneral_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_tiny_mizogeneral_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|390.1 MB|
+
+## References
+
+https://huggingface.co/AnalyticalRecon/whisper-tiny-mizoGeneral
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-whisper_tiny_tamil_parambharat_pipeline_ta.md b/docs/_posts/ahmedlone127/2024-09-09-whisper_tiny_tamil_parambharat_pipeline_ta.md
new file mode 100644
index 00000000000000..0beeb8e8479a1c
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-whisper_tiny_tamil_parambharat_pipeline_ta.md
@@ -0,0 +1,69 @@
+---
+layout: model
+title: Tamil whisper_tiny_tamil_parambharat_pipeline pipeline WhisperForCTC from parambharat
+author: John Snow Labs
+name: whisper_tiny_tamil_parambharat_pipeline
+date: 2024-09-09
+tags: [ta, open_source, pipeline, onnx]
+task: Automatic Speech Recognition
+language: ta
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_tiny_tamil_parambharat_pipeline` is a Tamil model originally trained by parambharat.
+
+{:.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/whisper_tiny_tamil_parambharat_pipeline_ta_5.5.0_3.0_1725844635904.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_tamil_parambharat_pipeline_ta_5.5.0_3.0_1725844635904.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
+
+pipeline = PretrainedPipeline("whisper_tiny_tamil_parambharat_pipeline", lang = "ta")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("whisper_tiny_tamil_parambharat_pipeline", lang = "ta")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_tiny_tamil_parambharat_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|ta|
+|Size:|391.0 MB|
+
+## References
+
+https://huggingface.co/parambharat/whisper-tiny-ta
+
+## Included Models
+
+- AudioAssembler
+- WhisperForCTC
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-whisper_tiny_tamil_parambharat_ta.md b/docs/_posts/ahmedlone127/2024-09-09-whisper_tiny_tamil_parambharat_ta.md
new file mode 100644
index 00000000000000..052956fedeb1c1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-whisper_tiny_tamil_parambharat_ta.md
@@ -0,0 +1,84 @@
+---
+layout: model
+title: Tamil whisper_tiny_tamil_parambharat WhisperForCTC from parambharat
+author: John Snow Labs
+name: whisper_tiny_tamil_parambharat
+date: 2024-09-09
+tags: [ta, open_source, onnx, asr, whisper]
+task: Automatic Speech Recognition
+language: ta
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: WhisperForCTC
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`whisper_tiny_tamil_parambharat` is a Tamil model originally trained by parambharat.
+
+{:.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/whisper_tiny_tamil_parambharat_ta_5.5.0_3.0_1725844616201.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_tamil_parambharat_ta_5.5.0_3.0_1725844616201.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
+     
+audioAssembler = AudioAssembler() \
+	.setInputCol("audio_content") \
+	.setOutputCol("audio_assembler")
+
+speechToText  = WhisperForCTC.pretrained("whisper_tiny_tamil_parambharat","ta") \
+     .setInputCols(["audio_assembler"]) \
+     .setOutputCol("text")
+
+pipeline = Pipeline().setStages([audioAssembler, speechToText])
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val audioAssembler = new DocumentAssembler()
+    .setInputCols("audio_content")
+    .setOutputCols("audio_assembler")
+
+val speechToText = WhisperForCTC.pretrained("whisper_tiny_tamil_parambharat", "ta")
+    .setInputCols(Array("audio_assembler")) 
+    .setOutputCol("text") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText))
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|whisper_tiny_tamil_parambharat|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[audio_assembler]|
+|Output Labels:|[text]|
+|Language:|ta|
+|Size:|390.9 MB|
+
+## References
+
+https://huggingface.co/parambharat/whisper-tiny-ta
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-xlm_roberta_base_balance_vietnam_aug_replace_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-xlm_roberta_base_balance_vietnam_aug_replace_bert_pipeline_en.md
new file mode 100644
index 00000000000000..f3920555c141a1
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-xlm_roberta_base_balance_vietnam_aug_replace_bert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_balance_vietnam_aug_replace_bert_pipeline pipeline XlmRoBertaForSequenceClassification from ThuyNT03
+author: John Snow Labs
+name: xlm_roberta_base_balance_vietnam_aug_replace_bert_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_balance_vietnam_aug_replace_bert_pipeline` is a English model originally trained by ThuyNT03.
+
+{:.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/xlm_roberta_base_balance_vietnam_aug_replace_bert_pipeline_en_5.5.0_3.0_1725871434510.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_balance_vietnam_aug_replace_bert_pipeline_en_5.5.0_3.0_1725871434510.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_balance_vietnam_aug_replace_bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_balance_vietnam_aug_replace_bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_balance_vietnam_aug_replace_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|794.6 MB|
+
+## References
+
+https://huggingface.co/ThuyNT03/xlm-roberta-base-Balance_VietNam-aug_replace_BERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-xlm_roberta_base_english_sentweet_derogatory_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-xlm_roberta_base_english_sentweet_derogatory_pipeline_en.md
new file mode 100644
index 00000000000000..92162dba46779e
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-xlm_roberta_base_english_sentweet_derogatory_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_english_sentweet_derogatory_pipeline pipeline XlmRoBertaForSequenceClassification from jayanta
+author: John Snow Labs
+name: xlm_roberta_base_english_sentweet_derogatory_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_english_sentweet_derogatory_pipeline` is a English model originally trained by jayanta.
+
+{:.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/xlm_roberta_base_english_sentweet_derogatory_pipeline_en_5.5.0_3.0_1725870724623.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_english_sentweet_derogatory_pipeline_en_5.5.0_3.0_1725870724623.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_english_sentweet_derogatory_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_english_sentweet_derogatory_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_english_sentweet_derogatory_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|785.8 MB|
+
+## References
+
+https://huggingface.co/jayanta/xlm-roberta-base-english-sentweet-derogatory
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-xlm_roberta_base_final_mixed_aug_replace_bert_2_en.md b/docs/_posts/ahmedlone127/2024-09-09-xlm_roberta_base_final_mixed_aug_replace_bert_2_en.md
new file mode 100644
index 00000000000000..ad7bfc70423377
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-xlm_roberta_base_final_mixed_aug_replace_bert_2_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_final_mixed_aug_replace_bert_2 XlmRoBertaForSequenceClassification from ThuyNT03
+author: John Snow Labs
+name: xlm_roberta_base_final_mixed_aug_replace_bert_2
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_final_mixed_aug_replace_bert_2` is a English model originally trained by ThuyNT03.
+
+{:.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/xlm_roberta_base_final_mixed_aug_replace_bert_2_en_5.5.0_3.0_1725871834187.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_mixed_aug_replace_bert_2_en_5.5.0_3.0_1725871834187.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_final_mixed_aug_replace_bert_2","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_final_mixed_aug_replace_bert_2", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_final_mixed_aug_replace_bert_2|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|795.6 MB|
+
+## References
+
+https://huggingface.co/ThuyNT03/xlm-roberta-base-Final_Mixed-aug_replace_BERT-2
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-xlm_roberta_base_final_mixed_aug_replace_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-xlm_roberta_base_final_mixed_aug_replace_bert_pipeline_en.md
new file mode 100644
index 00000000000000..e55b9a06365674
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-xlm_roberta_base_final_mixed_aug_replace_bert_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_final_mixed_aug_replace_bert_pipeline pipeline XlmRoBertaForSequenceClassification from ThuyNT03
+author: John Snow Labs
+name: xlm_roberta_base_final_mixed_aug_replace_bert_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_final_mixed_aug_replace_bert_pipeline` is a English model originally trained by ThuyNT03.
+
+{:.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/xlm_roberta_base_final_mixed_aug_replace_bert_pipeline_en_5.5.0_3.0_1725871573892.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_mixed_aug_replace_bert_pipeline_en_5.5.0_3.0_1725871573892.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_final_mixed_aug_replace_bert_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_final_mixed_aug_replace_bert_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_final_mixed_aug_replace_bert_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|795.6 MB|
+
+## References
+
+https://huggingface.co/ThuyNT03/xlm-roberta-base-Final_Mixed-aug_replace_BERT
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-xlm_roberta_base_final_vietnam_aug_insert_bert_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-xlm_roberta_base_final_vietnam_aug_insert_bert_1_pipeline_en.md
new file mode 100644
index 00000000000000..2c98776a5b92eb
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-xlm_roberta_base_final_vietnam_aug_insert_bert_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_final_vietnam_aug_insert_bert_1_pipeline pipeline XlmRoBertaForSequenceClassification from ThuyNT03
+author: John Snow Labs
+name: xlm_roberta_base_final_vietnam_aug_insert_bert_1_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_final_vietnam_aug_insert_bert_1_pipeline` is a English model originally trained by ThuyNT03.
+
+{:.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/xlm_roberta_base_final_vietnam_aug_insert_bert_1_pipeline_en_5.5.0_3.0_1725869992236.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_vietnam_aug_insert_bert_1_pipeline_en_5.5.0_3.0_1725869992236.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_final_vietnam_aug_insert_bert_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_final_vietnam_aug_insert_bert_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_final_vietnam_aug_insert_bert_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|794.2 MB|
+
+## References
+
+https://huggingface.co/ThuyNT03/xlm-roberta-base-Final_VietNam-aug_insert_BERT-1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-xlm_roberta_base_germeval21_toxic_with_task_specific_pretraining_and_data_augmentation_en.md b/docs/_posts/ahmedlone127/2024-09-09-xlm_roberta_base_germeval21_toxic_with_task_specific_pretraining_and_data_augmentation_en.md
new file mode 100644
index 00000000000000..db1a4bf9a2eda9
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-xlm_roberta_base_germeval21_toxic_with_task_specific_pretraining_and_data_augmentation_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_germeval21_toxic_with_task_specific_pretraining_and_data_augmentation XlmRoBertaForSequenceClassification from airKlizz
+author: John Snow Labs
+name: xlm_roberta_base_germeval21_toxic_with_task_specific_pretraining_and_data_augmentation
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_germeval21_toxic_with_task_specific_pretraining_and_data_augmentation` is a English model originally trained by airKlizz.
+
+{:.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/xlm_roberta_base_germeval21_toxic_with_task_specific_pretraining_and_data_augmentation_en_5.5.0_3.0_1725870419756.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_germeval21_toxic_with_task_specific_pretraining_and_data_augmentation_en_5.5.0_3.0_1725870419756.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_germeval21_toxic_with_task_specific_pretraining_and_data_augmentation","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_germeval21_toxic_with_task_specific_pretraining_and_data_augmentation", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_germeval21_toxic_with_task_specific_pretraining_and_data_augmentation|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|905.8 MB|
+
+## References
+
+https://huggingface.co/airKlizz/xlm-roberta-base-germeval21-toxic-with-task-specific-pretraining-and-data-augmentation
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-xlm_roberta_base_germeval21_toxic_with_task_specific_pretraining_and_data_augmentation_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-xlm_roberta_base_germeval21_toxic_with_task_specific_pretraining_and_data_augmentation_pipeline_en.md
new file mode 100644
index 00000000000000..5e08948098b6f5
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-xlm_roberta_base_germeval21_toxic_with_task_specific_pretraining_and_data_augmentation_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_germeval21_toxic_with_task_specific_pretraining_and_data_augmentation_pipeline pipeline XlmRoBertaForSequenceClassification from airKlizz
+author: John Snow Labs
+name: xlm_roberta_base_germeval21_toxic_with_task_specific_pretraining_and_data_augmentation_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_germeval21_toxic_with_task_specific_pretraining_and_data_augmentation_pipeline` is a English model originally trained by airKlizz.
+
+{:.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/xlm_roberta_base_germeval21_toxic_with_task_specific_pretraining_and_data_augmentation_pipeline_en_5.5.0_3.0_1725870480859.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_germeval21_toxic_with_task_specific_pretraining_and_data_augmentation_pipeline_en_5.5.0_3.0_1725870480859.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_germeval21_toxic_with_task_specific_pretraining_and_data_augmentation_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_germeval21_toxic_with_task_specific_pretraining_and_data_augmentation_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_germeval21_toxic_with_task_specific_pretraining_and_data_augmentation_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|905.8 MB|
+
+## References
+
+https://huggingface.co/airKlizz/xlm-roberta-base-germeval21-toxic-with-task-specific-pretraining-and-data-augmentation
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-xlm_roberta_base_lr0_001_seed42_esp_hau_eng_train_en.md b/docs/_posts/ahmedlone127/2024-09-09-xlm_roberta_base_lr0_001_seed42_esp_hau_eng_train_en.md
new file mode 100644
index 00000000000000..ed3e2c2c5d48e7
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-xlm_roberta_base_lr0_001_seed42_esp_hau_eng_train_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English xlm_roberta_base_lr0_001_seed42_esp_hau_eng_train XlmRoBertaForSequenceClassification from shanhy
+author: John Snow Labs
+name: xlm_roberta_base_lr0_001_seed42_esp_hau_eng_train
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, xlm_roberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: XlmRoBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_lr0_001_seed42_esp_hau_eng_train` is a English model originally trained by shanhy.
+
+{:.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/xlm_roberta_base_lr0_001_seed42_esp_hau_eng_train_en_5.5.0_3.0_1725869810636.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr0_001_seed42_esp_hau_eng_train_en_5.5.0_3.0_1725869810636.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_lr0_001_seed42_esp_hau_eng_train","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_lr0_001_seed42_esp_hau_eng_train", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_lr0_001_seed42_esp_hau_eng_train|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|846.5 MB|
+
+## References
+
+https://huggingface.co/shanhy/xlm-roberta-base_lr0.001_seed42_esp-hau-eng_train
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-xlm_roberta_base_lr0_001_seed42_esp_hau_eng_train_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-xlm_roberta_base_lr0_001_seed42_esp_hau_eng_train_pipeline_en.md
new file mode 100644
index 00000000000000..04670dc04d430a
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-xlm_roberta_base_lr0_001_seed42_esp_hau_eng_train_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English xlm_roberta_base_lr0_001_seed42_esp_hau_eng_train_pipeline pipeline XlmRoBertaForSequenceClassification from shanhy
+author: John Snow Labs
+name: xlm_roberta_base_lr0_001_seed42_esp_hau_eng_train_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_lr0_001_seed42_esp_hau_eng_train_pipeline` is a English model originally trained by shanhy.
+
+{:.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/xlm_roberta_base_lr0_001_seed42_esp_hau_eng_train_pipeline_en_5.5.0_3.0_1725869888953.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr0_001_seed42_esp_hau_eng_train_pipeline_en_5.5.0_3.0_1725869888953.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
+
+pipeline = PretrainedPipeline("xlm_roberta_base_lr0_001_seed42_esp_hau_eng_train_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("xlm_roberta_base_lr0_001_seed42_esp_hau_eng_train_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|xlm_roberta_base_lr0_001_seed42_esp_hau_eng_train_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|846.5 MB|
+
+## References
+
+https://huggingface.co/shanhy/xlm-roberta-base_lr0.001_seed42_esp-hau-eng_train
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- XlmRoBertaForSequenceClassification
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-yelp_polarity_microsoft_deberta_v3_large_seed_1_en.md b/docs/_posts/ahmedlone127/2024-09-09-yelp_polarity_microsoft_deberta_v3_large_seed_1_en.md
new file mode 100644
index 00000000000000..97abdccb485828
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-yelp_polarity_microsoft_deberta_v3_large_seed_1_en.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: English yelp_polarity_microsoft_deberta_v3_large_seed_1 DeBertaForSequenceClassification from utahnlp
+author: John Snow Labs
+name: yelp_polarity_microsoft_deberta_v3_large_seed_1
+date: 2024-09-09
+tags: [en, open_source, onnx, sequence_classification, deberta]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: DeBertaForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yelp_polarity_microsoft_deberta_v3_large_seed_1` is a English model originally trained by utahnlp.
+
+{:.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/yelp_polarity_microsoft_deberta_v3_large_seed_1_en_5.5.0_3.0_1725879484840.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yelp_polarity_microsoft_deberta_v3_large_seed_1_en_5.5.0_3.0_1725879484840.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
+     
+documentAssembler = DocumentAssembler() \
+    .setInputCol('text') \
+    .setOutputCol('document')
+    
+tokenizer = Tokenizer() \
+    .setInputCols(['document']) \
+    .setOutputCol('token')
+
+sequenceClassifier  = DeBertaForSequenceClassification.pretrained("yelp_polarity_microsoft_deberta_v3_large_seed_1","en") \
+     .setInputCols(["documents","token"]) \
+     .setOutputCol("class")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier])
+data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text")
+pipelineModel = pipeline.fit(data)
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCols("text")
+    .setOutputCols("document")
+    
+val tokenizer = new Tokenizer()
+    .setInputCols(Array("document"))
+    .setOutputCol("token")
+
+val sequenceClassifier = DeBertaForSequenceClassification.pretrained("yelp_polarity_microsoft_deberta_v3_large_seed_1", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("class") 
+    
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier))
+val data = Seq("I love spark-nlp").toDS.toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|yelp_polarity_microsoft_deberta_v3_large_seed_1|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/utahnlp/yelp_polarity_microsoft_deberta-v3-large_seed-1
\ No newline at end of file
diff --git a/docs/_posts/ahmedlone127/2024-09-09-yelp_polarity_microsoft_deberta_v3_large_seed_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-yelp_polarity_microsoft_deberta_v3_large_seed_1_pipeline_en.md
new file mode 100644
index 00000000000000..a2828a42441c60
--- /dev/null
+++ b/docs/_posts/ahmedlone127/2024-09-09-yelp_polarity_microsoft_deberta_v3_large_seed_1_pipeline_en.md
@@ -0,0 +1,70 @@
+---
+layout: model
+title: English yelp_polarity_microsoft_deberta_v3_large_seed_1_pipeline pipeline DeBertaForSequenceClassification from utahnlp
+author: John Snow Labs
+name: yelp_polarity_microsoft_deberta_v3_large_seed_1_pipeline
+date: 2024-09-09
+tags: [en, open_source, pipeline, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.5.0
+spark_version: 3.0
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained DeBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yelp_polarity_microsoft_deberta_v3_large_seed_1_pipeline` is a English model originally trained by utahnlp.
+
+{:.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/yelp_polarity_microsoft_deberta_v3_large_seed_1_pipeline_en_5.5.0_3.0_1725879571713.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yelp_polarity_microsoft_deberta_v3_large_seed_1_pipeline_en_5.5.0_3.0_1725879571713.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
+
+pipeline = PretrainedPipeline("yelp_polarity_microsoft_deberta_v3_large_seed_1_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("yelp_polarity_microsoft_deberta_v3_large_seed_1_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|yelp_polarity_microsoft_deberta_v3_large_seed_1_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|1.6 GB|
+
+## References
+
+https://huggingface.co/utahnlp/yelp_polarity_microsoft_deberta-v3-large_seed-1
+
+## Included Models
+
+- DocumentAssembler
+- TokenizerModel
+- DeBertaForSequenceClassification
\ No newline at end of file