{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-22-match_datetime_en.md b/docs/_posts/ahmedlone127/2023-05-22-match_datetime_en.md
index 57932b42257f82..f80a11e7fa7852 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-match_datetime_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-match_datetime_en.md
@@ -32,35 +32,7 @@ DateMatcher based on yyyy/MM/dd
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-pipeline_local = PretrainedPipeline('match_datetime')
-
-tres = pipeline_local.fullAnnotate(input_list)[0]
-for dte in tres['date']:
- sent = tres['sentence'][int(dte.metadata['sentence'])]
- print (f'text/chunk {sent.result[dte.begin:dte.end+1]} | mapped_date: {dte.result}')
-```
-```scala
-
-import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline import com.johnsnowlabs.nlp.SparkNLP
-SparkNLP.version()
-
-val testData = spark.createDataFrame(Seq( (1, "David visited the restaurant yesterday with his family.
-He also visited and the day before, but at that time he was alone.
-David again visited today with his colleagues.
-He and his friends really liked the food and hoped to visit again tomorrow."))).toDF("id", "text")
-
-val pipeline = PretrainedPipeline("match_datetime", lang="en")
-
-val annotation = pipeline.transform(testData)
-
-annotation.show()
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-22-match_pattern_en.md b/docs/_posts/ahmedlone127/2023-05-22-match_pattern_en.md
index 4c55bc1f6ce271..481caef65b1f88 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-match_pattern_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-match_pattern_en.md
@@ -33,16 +33,7 @@ The match_pattern is a pretrained pipeline that we can use to process text with
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-from sparknlp.pretrained import PretrainedPipeline
-pipeline = PretrainedPipeline("match_pattern", "en", "clinical/models")
- result = pipeline.annotate("""I love johnsnowlabs! """)
-```
-
-
{:.model-param}
diff --git a/docs/_posts/ahmedlone127/2023-05-22-movies_sentiment_analysis_en.md b/docs/_posts/ahmedlone127/2023-05-22-movies_sentiment_analysis_en.md
index cc0ac4fc6f624c..560156c89d760a 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-movies_sentiment_analysis_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-movies_sentiment_analysis_en.md
@@ -33,16 +33,7 @@ The movies_sentiment_analysis is a pretrained pipeline that we can use to proces
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-from sparknlp.pretrained import PretrainedPipeline
-pipeline = PretrainedPipeline("movies_sentiment_analysis", "en")
-result = pipeline.annotate("""I love johnsnowlabs! """)
-```
-
-
{:.model-param}
diff --git a/docs/_posts/ahmedlone127/2023-05-22-nerdl_fewnerd_100d_pipeline_en.md b/docs/_posts/ahmedlone127/2023-05-22-nerdl_fewnerd_100d_pipeline_en.md
index 9ca480fccdef9d..0b5111e8d0f896 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-nerdl_fewnerd_100d_pipeline_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-nerdl_fewnerd_100d_pipeline_en.md
@@ -34,21 +34,7 @@ This pretrained pipeline is built on Few-NERD model and it detects :
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-fewnerd_pipeline = PretrainedPipeline("nerdl_fewnerd_subentity_100d_pipeline", lang = "en")
-
-fewnerd_pipeline.annotate("""The Double Down is a sandwich offered by Kentucky Fried Chicken restaurants. He did not see active service again until 1882, when he took part in the Anglo-Egyptian War, and was present at the battle of Tell El Kebir (September 1882), for which he was mentioned in dispatches, received the Egypt Medal with clasp and the 3rd class of the Order of Medjidie, and was appointed a Companion of the Order of the Bath (CB).""")
-```
-```scala
-
-val pipeline = new PretrainedPipeline("nerdl_fewnerd_subentity_100d_pipeline", lang = "en")
-val result = pipeline.fullAnnotate("The Double Down is a sandwich offered by Kentucky Fried Chicken restaurants. He did not see active service again until 1882, when he took part in the Anglo-Egyptian War, and was present at the battle of Tell El Kebir (September 1882), for which he was mentioned in dispatches, received the Egypt Medal with clasp and the 3rd class of the Order of Medjidie, and was appointed a Companion of the Order of the Bath (CB).")(0)
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-22-nerdl_fewnerd_subentity_100d_pipeline_en.md b/docs/_posts/ahmedlone127/2023-05-22-nerdl_fewnerd_subentity_100d_pipeline_en.md
index 6337f0136a984d..86920d4eef13a9 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-nerdl_fewnerd_subentity_100d_pipeline_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-nerdl_fewnerd_subentity_100d_pipeline_en.md
@@ -32,21 +32,7 @@ This pretrained pipeline is built on Few-NERD/inter public dataset and it extrac
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-fewnerd_pipeline = PretrainedPipeline("nerdl_fewnerd_subentity_100d_pipeline", lang = "en")
-
-fewnerd_pipeline.annotate("""12 Corazones ('12 Hearts') is Spanish-language dating game show produced in the United States for the television network Telemundo since January 2005, based on its namesake Argentine TV show format. The show is filmed in Los Angeles and revolves around the twelve Zodiac signs that identify each contestant. In 2008, Ho filmed a cameo in the Steven Spielberg feature film The Cloverfield Paradox, as a news pundit.""")
-```
-```scala
-
-val pipeline = new PretrainedPipeline("nerdl_fewnerd_subentity_100d_pipeline", lang = "en")
-val result = pipeline.fullAnnotate("12 Corazones ('12 Hearts') is Spanish-language dating game show produced in the United States for the television network Telemundo since January 2005, based on its namesake Argentine TV show format. The show is filmed in Los Angeles and revolves around the twelve Zodiac signs that identify each contestant. In 2008, Ho filmed a cameo in the Steven Spielberg feature film The Cloverfield Paradox, as a news pundit.")(0)
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-22-nerdl_restaurant_100d_pipeline_en.md b/docs/_posts/ahmedlone127/2023-05-22-nerdl_restaurant_100d_pipeline_en.md
index 15f6f43e5b8103..a40cc0735dda25 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-nerdl_restaurant_100d_pipeline_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-nerdl_restaurant_100d_pipeline_en.md
@@ -32,21 +32,7 @@ This pretrained pipeline is built on the top of [nerdl_restaurant_100d](https://
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-restaurant_pipeline = PretrainedPipeline("nerdl_restaurant_100d_pipeline", lang = "en")
-
-restaurant_pipeline.annotate("Hong Kong’s favourite pasta bar also offers one of the most reasonably priced lunch sets in town! With locations spread out all over the territory Sha Tin – Pici’s formidable lunch menu reads like a highlight reel of the restaurant. Choose from starters like the burrata and arugula salad or freshly tossed tuna tartare, and reliable handmade pasta dishes like pappardelle. Finally, round out your effortless Italian meal with a tidy one-pot tiramisu, of course, an espresso to power you through the rest of the day.")
-```
-```scala
-
-val restaurant_pipeline = new PretrainedPipeline("nerdl_restaurant_100d_pipeline", lang = "en")
-restaurant_pipeline.annotate("Hong Kong’s favourite pasta bar also offers one of the most reasonably priced lunch sets in town! With locations spread out all over the territory Sha Tin – Pici’s formidable lunch menu reads like a highlight reel of the restaurant. Choose from starters like the burrata and arugula salad or freshly tossed tuna tartare, and reliable handmade pasta dishes like pappardelle. Finally, round out your effortless Italian meal with a tidy one-pot tiramisu, of course, an espresso to power you through the rest of the day.")
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_bert_base_en.md b/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_bert_base_en.md
index d63528bb521f24..9bf91e1036a342 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_bert_base_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_bert_base_en.md
@@ -34,35 +34,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('onto_recognize_entities_bert_base', lang = 'en')
-annotations = pipeline.fullAnnotate(""Hello from John Snow Labs ! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("onto_recognize_entities_bert_base", lang = "en")
-val result = pipeline.fullAnnotate("Hello from John Snow Labs ! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hello from John Snow Labs ! ""]
-result_df = nlu.load('en.ner.onto.bert.base').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_bert_large_en.md b/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_bert_large_en.md
index f362f3d323a62b..7b6ec2cf54212f 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_bert_large_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_bert_large_en.md
@@ -34,35 +34,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('onto_recognize_entities_bert_large', lang = 'en')
-annotations = pipeline.fullAnnotate(""Hello from John Snow Labs ! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("onto_recognize_entities_bert_large", lang = "en")
-val result = pipeline.fullAnnotate("Hello from John Snow Labs ! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hello from John Snow Labs ! ""]
-result_df = nlu.load('en.ner.onto.bert.large').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_bert_medium_en.md b/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_bert_medium_en.md
index 519d1c16b5c60a..6d53255765848b 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_bert_medium_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_bert_medium_en.md
@@ -34,35 +34,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('onto_recognize_entities_bert_medium', lang = 'en')
-annotations = pipeline.fullAnnotate(""Hello from John Snow Labs ! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("onto_recognize_entities_bert_medium", lang = "en")
-val result = pipeline.fullAnnotate("Hello from John Snow Labs ! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hello from John Snow Labs ! ""]
-result_df = nlu.load('en.ner.onto.bert.medium').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_bert_mini_en.md b/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_bert_mini_en.md
index 9bb36244046f97..e3e30b745e284e 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_bert_mini_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_bert_mini_en.md
@@ -34,35 +34,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('onto_recognize_entities_bert_mini', lang = 'en')
-annotations = pipeline.fullAnnotate(""Hello from John Snow Labs ! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("onto_recognize_entities_bert_mini", lang = "en")
-val result = pipeline.fullAnnotate("Hello from John Snow Labs ! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hello from John Snow Labs ! ""]
-result_df = nlu.load('en.ner.onto.bert.mini').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_bert_small_en.md b/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_bert_small_en.md
index 07de2dd5f53614..6fa55447acd74c 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_bert_small_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_bert_small_en.md
@@ -33,35 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('onto_recognize_entities_bert_small', lang = 'en')
-annotations = pipeline.fullAnnotate(""Hello from John Snow Labs ! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("onto_recognize_entities_bert_small", lang = "en")
-val result = pipeline.fullAnnotate("Hello from John Snow Labs ! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hello from John Snow Labs ! ""]
-result_df = nlu.load('en.ner.onto.bert.small').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_bert_tiny_en.md b/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_bert_tiny_en.md
index 1a722c34fa70bd..d7f03e348d7154 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_bert_tiny_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_bert_tiny_en.md
@@ -34,35 +34,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('onto_recognize_entities_bert_tiny', lang = 'en')
-annotations = pipeline.fullAnnotate(""Hello from John Snow Labs ! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("onto_recognize_entities_bert_tiny", lang = "en")
-val result = pipeline.fullAnnotate("Hello from John Snow Labs ! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hello from John Snow Labs ! ""]
-result_df = nlu.load('en.ner.onto.bert.tiny').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_electra_base_en.md b/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_electra_base_en.md
index 905ff995657472..31f126c38a1bac 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_electra_base_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_electra_base_en.md
@@ -34,35 +34,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('onto_recognize_entities_electra_base', lang = 'en')
-annotations = pipeline.fullAnnotate(""Hello from John Snow Labs ! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("onto_recognize_entities_electra_base", lang = "en")
-val result = pipeline.fullAnnotate("Hello from John Snow Labs ! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hello from John Snow Labs ! ""]
-result_df = nlu.load('en.ner.onto.electra.base').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_electra_large_en.md b/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_electra_large_en.md
index 1e68b4e623705d..7fd51a3c25d637 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_electra_large_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_electra_large_en.md
@@ -34,35 +34,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipeline
-pipeline = PretrainedPipeline('onto_recognize_entities_electra_large', lang = 'en')
-annotations = pipeline.fullAnnotate("Hello from John Snow Labs!")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("onto_recognize_entities_electra_large", lang = "en")
-val result = pipeline.fullAnnotate("Hello from John Snow Labs ! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hello from John Snow Labs ! ""]
-result_df = nlu.load('en.ner.onto.large').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_electra_small_en.md b/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_electra_small_en.md
index 1177daf831daf2..4a212a1ced1461 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_electra_small_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_electra_small_en.md
@@ -33,35 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('onto_recognize_entities_electra_small', lang = 'en')
-annotations = pipeline.fullAnnotate(""Hello from John Snow Labs ! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("onto_recognize_entities_electra_small", lang = "en")
-val result = pipeline.fullAnnotate("Hello from John Snow Labs ! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hello from John Snow Labs ! ""]
-result_df = nlu.load('en.ner.onto.electra.small').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_lg_en.md b/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_lg_en.md
index a03017071dfa89..b0832c47fbf9bc 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_lg_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_lg_en.md
@@ -33,25 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-from sparknlp.pretrained import PretrainedPipeline
-pipeline = PretrainedPipeline("onto_recognize_entities_lg", "en")
-
-result = pipeline.annotate("""I love johnsnowlabs! """)
-```
-
-{:.nlu-block}
-```python
-import nlu
-nlu.load("en.ner.onto.lg").predict("""I love johnsnowlabs! """)
-```
-
-
-
{:.model-param}
diff --git a/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_sm_en.md b/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_sm_en.md
index 9895cd6398d85c..74528f8b336b37 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_sm_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-onto_recognize_entities_sm_en.md
@@ -33,35 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('onto_recognize_entities_sm', lang = 'en')
-annotations = pipeline.fullAnnotate(""Hello from John Snow Labs ! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("onto_recognize_entities_sm", lang = "en")
-val result = pipeline.fullAnnotate("Hello from John Snow Labs ! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hello from John Snow Labs ! ""]
-result_df = nlu.load('en.ner.onto.sm').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-22-pos_ud_bokmaal_nb.md b/docs/_posts/ahmedlone127/2023-05-22-pos_ud_bokmaal_nb.md
index e5c889d05ef3a7..690fbfa93c7bfe 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-pos_ud_bokmaal_nb.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-pos_ud_bokmaal_nb.md
@@ -34,39 +34,7 @@ This model was trained using the dataset available at https://universaldependenc
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-pos = PerceptronModel.pretrained("pos_ud_bokmaal", "nb") \
- .setInputCols(["document", "token"]) \
- .setOutputCol("pos")
-
-nlp_pipeline = Pipeline(stages=[document_assembler, sentence_detector, tokenizer, pos])
-light_pipeline = LightPipeline(nlp_pipeline.fit(spark.createDataFrame([['']]).toDF("text")))
-results = light_pipeline.fullAnnotate("Annet enn å være kongen i nord, er John Snow en engelsk lege og en leder innen utvikling av anestesi og medisinsk hygiene.")
-```
-```scala
-
-val pos = PerceptronModel.pretrained("pos_ud_bokmaal", "nb")
- .setInputCols(Array("document", "token"))
- .setOutputCol("pos")
-
-val pipeline = new Pipeline().setStages(Array(document_assembler, sentence_detector, tokenizer, pos))
-val data = Seq("Annet enn å være kongen i nord, er John Snow en engelsk lege og en leder innen utvikling av anestesi og medisinsk hygiene.").toDF("text")
-val result = pipeline.fit(data).transform(data)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = ["""Annet enn å være kongen i nord, er John Snow en engelsk lege og en leder innen utvikling av anestesi og medisinsk hygiene."""]
-pos_df = nlu.load('nb.pos.ud_bokmaal').predict(text)
-pos_df
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-22-recognize_entities_bert_en.md b/docs/_posts/ahmedlone127/2023-05-22-recognize_entities_bert_en.md
index ac7290c2c2f439..ad32d266f1e076 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-recognize_entities_bert_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-recognize_entities_bert_en.md
@@ -34,35 +34,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('recognize_entities_bert', lang = 'en')
-annotations = pipeline.fullAnnotate(""Hello from John Snow Labs ! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("recognize_entities_bert", lang = "en")
-val result = pipeline.fullAnnotate("Hello from John Snow Labs ! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hello from John Snow Labs ! ""]
-result_df = nlu.load('en.ner.bert').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-22-recognize_entities_dl_en.md b/docs/_posts/ahmedlone127/2023-05-22-recognize_entities_dl_en.md
index ee25fc3f75a502..9c02e144ca8c26 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-recognize_entities_dl_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-recognize_entities_dl_en.md
@@ -34,35 +34,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('recognize_entities_dl', lang = 'en')
-annotations = pipeline.fullAnnotate(""Hello from John Snow Labs ! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("recognize_entities_dl", lang = "en")
-val result = pipeline.fullAnnotate("Hello from John Snow Labs ! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hello from John Snow Labs ! ""]
-result_df = nlu.load('en.ner').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-22-recognize_entities_dl_fa.md b/docs/_posts/ahmedlone127/2023-05-22-recognize_entities_dl_fa.md
index 722e3d58623246..51a551c4114919 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-recognize_entities_dl_fa.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-recognize_entities_dl_fa.md
@@ -32,37 +32,7 @@ The explain_document_dl is a pretrained pipeline that we can use to process text
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipeline
-
-pipeline = PretrainedPipeline('recognize_entities_dl', lang = 'fa')
-
-annotations = pipeline.fullAnnotate("""به گزارش خبرنگار ایرنا ، بر اساس تصمیم این مجمع ، محمد قمی نماینده مردم پاکدشت به عنوان رئیس و علیاکبر موسوی خوئینی و شمسالدین وهابی نمایندگان مردم تهران به عنوان نواب رئیس انتخاب شدند""")[0]
-
-annotations.keys()
-```
-```scala
-
-val pipeline = new PretrainedPipeline("recognize_entities_dl", lang = "fa")
-val result = pipeline.fullAnnotate("""به گزارش خبرنگار ایرنا ، بر اساس تصمیم این مجمع ، محمد قمی نماینده مردم پاکدشت به عنوان رئیس و علیاکبر موسوی خوئینی و شمسالدین وهابی نمایندگان مردم تهران به عنوان نواب رئیس انتخاب شدند""")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-
-text = ["""به گزارش خبرنگار ایرنا ، بر اساس تصمیم این مجمع ، محمد قمی نماینده مردم پاکدشت به عنوان رئیس و علیاکبر موسوی خوئینی و شمسالدین وهابی نمایندگان مردم تهران به عنوان نواب رئیس انتخاب شدند"""]
-
-result_df = nlu.load('fa.recognize_entities_dl').predict(text)
-
-result_df
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-22-roberta_base_token_classifier_ontonotes_pipeline_en.md b/docs/_posts/ahmedlone127/2023-05-22-roberta_base_token_classifier_ontonotes_pipeline_en.md
index 0ec192b82de752..5fab17c3b9af2b 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-roberta_base_token_classifier_ontonotes_pipeline_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-roberta_base_token_classifier_ontonotes_pipeline_en.md
@@ -32,21 +32,7 @@ This pretrained pipeline is built on the top of [roberta_base_token_classifier_o
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-pipeline = PretrainedPipeline("roberta_base_token_classifier_ontonotes_pipeline", lang = "en")
-
-pipeline.annotate("My name is John and I have been working at John Snow Labs since November 2020.")
-```
-```scala
-
-val pipeline = new PretrainedPipeline("roberta_base_token_classifier_ontonotes_pipeline", lang = "en")
-pipeline.annotate("My name is John and I have been working at John Snow Labs since November 2020."))
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-22-roberta_large_token_classifier_conll03_pipeline_en.md b/docs/_posts/ahmedlone127/2023-05-22-roberta_large_token_classifier_conll03_pipeline_en.md
index a7d710875988c0..1ea8fa9a308f8d 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-roberta_large_token_classifier_conll03_pipeline_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-roberta_large_token_classifier_conll03_pipeline_en.md
@@ -32,23 +32,7 @@ This pretrained pipeline is built on the top of [roberta_large_token_classifier_
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-
-pipeline = PretrainedPipeline("roberta_large_token_classifier_conll03_pipeline", lang = "en")
-
-pipeline.annotate("My name is John and I work at John Snow Labs.")
-```
-```scala
-
-
-val pipeline = new PretrainedPipeline("roberta_large_token_classifier_conll03_pipeline", lang = "en")
-pipeline.annotate("My name is John and I work at John Snow Labs."))
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-22-roberta_token_classifier_bne_capitel_ner_pipeline_es.md b/docs/_posts/ahmedlone127/2023-05-22-roberta_token_classifier_bne_capitel_ner_pipeline_es.md
index ff1f64782cf1ee..3afc986f076815 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-roberta_token_classifier_bne_capitel_ner_pipeline_es.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-roberta_token_classifier_bne_capitel_ner_pipeline_es.md
@@ -32,21 +32,7 @@ This pretrained pipeline is built on the top of [roberta_token_classifier_bne_ca
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-pipeline = PretrainedPipeline("roberta_token_classifier_bne_capitel_ner_pipeline", lang = "es")
-
-pipeline.annotate("Me llamo Antonio y trabajo en la fábrica de Mercedes-Benz en Madrid.")
-```
-```scala
-
-val pipeline = new PretrainedPipeline("roberta_token_classifier_bne_capitel_ner_pipeline", lang = "es")
-pipeline.annotate("Me llamo Antonio y trabajo en la fábrica de Mercedes-Benz en Madrid.")
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-22-roberta_token_classifier_icelandic_ner_pipeline_is.md b/docs/_posts/ahmedlone127/2023-05-22-roberta_token_classifier_icelandic_ner_pipeline_is.md
index 61688280e98e16..9920b51285fa58 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-roberta_token_classifier_icelandic_ner_pipeline_is.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-roberta_token_classifier_icelandic_ner_pipeline_is.md
@@ -32,21 +32,7 @@ This pretrained pipeline is built on the top of [roberta_token_classifier_icelan
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-pipeline = PretrainedPipeline("roberta_token_classifier_icelandic_ner_pipeline", lang = "is")
-
-pipeline.annotate("Ég heiti Peter Fergusson. Ég hef búið í New York síðan í október 2011 og unnið hjá Tesla Motor og þénað 100K $ á ári.")
-```
-```scala
-
-val pipeline = new PretrainedPipeline("roberta_token_classifier_icelandic_ner_pipeline", lang = "is")
-pipeline.annotate("Ég heiti Peter Fergusson. Ég hef búið í New York síðan í október 2011 og unnið hjá Tesla Motor og þénað 100K $ á ári.")
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-22-roberta_token_classifier_timex_semeval_pipeline_en.md b/docs/_posts/ahmedlone127/2023-05-22-roberta_token_classifier_timex_semeval_pipeline_en.md
index 93eb4f1b9a89a0..846081aa6031da 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-roberta_token_classifier_timex_semeval_pipeline_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-roberta_token_classifier_timex_semeval_pipeline_en.md
@@ -32,23 +32,7 @@ This pretrained pipeline is built on the top of [roberta_token_classifier_timex_
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-
-timex_pipeline = PretrainedPipeline("roberta_token_classifier_timex_semeval_pipeline", lang = "en")
-
-timex_pipeline.annotate("Model training was started at 22:12C and it took 3 days from Tuesday to Friday.")
-```
-```scala
-
-
-val timex_pipeline = new PretrainedPipeline("roberta_token_classifier_timex_semeval_pipeline", lang = "en")
-timex_pipeline.annotate("Model training was started at 22:12C and it took 3 days from Tuesday to Friday.")
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-22-spellcheck_dl_pipeline_en.md b/docs/_posts/ahmedlone127/2023-05-22-spellcheck_dl_pipeline_en.md
index 02d60cf8b49fa2..9d2b944659aaf8 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-spellcheck_dl_pipeline_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-spellcheck_dl_pipeline_en.md
@@ -32,27 +32,7 @@ This pretrained spellchecker pipeline is built on the top of [spellcheck_dl](htt
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-
-pipeline = PretrainedPipeline("spellcheck_dl_pipeline", lang = "en")
-
-text = ["During the summer we have the best ueather.", "I have a black ueather jacket, so nice."]
-
-pipeline.annotate(text)
-```
-```scala
-
-
-val pipeline = new PretrainedPipeline("spellcheck_dl_pipeline", lang = "en")
-val example = Array("During the summer we have the best ueather.", "I have a black ueather jacket, so nice.")
-
-pipeline.annotate(example)
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-22-text_cleaning_en.md b/docs/_posts/ahmedlone127/2023-05-22-text_cleaning_en.md
index bd21c3c74648b7..191bb5e3da0837 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-text_cleaning_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-text_cleaning_en.md
@@ -33,16 +33,7 @@ The text_cleaning is a pretrained pipeline that we can use to process text with
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-from sparknlp.pretrained import PretrainedPipeline
-pipeline = PretrainedPipeline("text_cleaning", "en")
-result = pipeline.annotate("""I love johnsnowlabs! """)
-```
-
-
{:.model-param}
diff --git a/docs/_posts/ahmedlone127/2023-05-22-xlm_roberta_base_token_classifier_conll03_pipeline_en.md b/docs/_posts/ahmedlone127/2023-05-22-xlm_roberta_base_token_classifier_conll03_pipeline_en.md
index b01501066476f8..bd7c77c8df7002 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-xlm_roberta_base_token_classifier_conll03_pipeline_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-xlm_roberta_base_token_classifier_conll03_pipeline_en.md
@@ -32,23 +32,7 @@ This pretrained pipeline is built on the top of [xlm_roberta_base_token_classifi
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-
-pipeline = PretrainedPipeline("xlm_roberta_base_token_classifier_conll03_pipeline", lang = "en")
-
-pipeline.annotate("My name is John and I work at John Snow Labs.")
-```
-```scala
-
-
-val pipeline = new PretrainedPipeline("xlm_roberta_base_token_classifier_conll03_pipeline", lang = "en")
-pipeline.annotate("My name is John and I work at John Snow Labs.")
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-22-xlm_roberta_base_token_classifier_ontonotes_pipeline_en.md b/docs/_posts/ahmedlone127/2023-05-22-xlm_roberta_base_token_classifier_ontonotes_pipeline_en.md
index 9b0a4e00a3cbec..c62562d48e60ad 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-xlm_roberta_base_token_classifier_ontonotes_pipeline_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-xlm_roberta_base_token_classifier_ontonotes_pipeline_en.md
@@ -32,23 +32,7 @@ This pretrained pipeline is built on the top of [xlm_roberta_base_token_classifi
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-
-pipeline = PretrainedPipeline("xlm_roberta_base_token_classifier_ontonotes_pipeline", lang = "en")
-
-pipeline.annotate("My name is John and I have been working at John Snow Labs since November 2020.")
-```
-```scala
-
-
-val pipeline = new PretrainedPipeline("xlm_roberta_base_token_classifier_ontonotes_pipeline", lang = "en")
-pipeline.annotate("My name is John and I have been working at John Snow Labs since November 2020.")
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-22-xlm_roberta_large_token_classifier_conll03_pipeline_de.md b/docs/_posts/ahmedlone127/2023-05-22-xlm_roberta_large_token_classifier_conll03_pipeline_de.md
index a5cde6f39d05a4..ee9bd6e7dc8675 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-xlm_roberta_large_token_classifier_conll03_pipeline_de.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-xlm_roberta_large_token_classifier_conll03_pipeline_de.md
@@ -32,21 +32,7 @@ This pretrained pipeline is built on the top of [xlm_roberta_large_token_classif
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-pipeline = PretrainedPipeline("xlm_roberta_large_token_classifier_conll03_pipeline", lang = "de")
-
-pipeline.annotate("Ibser begann seine Karriere beim ASK Ebreichsdorf. 2004 wechselte er zu Admira Wacker Mödling, wo er auch in der Akademie spielte.")
-```
-```scala
-
-val pipeline = new PretrainedPipeline("xlm_roberta_large_token_classifier_conll03_pipeline", lang = "de")
-pipeline.annotate("Ibser begann seine Karriere beim ASK Ebreichsdorf. 2004 wechselte er zu Admira Wacker Mödling, wo er auch in der Akademie spielte.")
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-22-xlm_roberta_large_token_classifier_hrl_pipeline_xx.md b/docs/_posts/ahmedlone127/2023-05-22-xlm_roberta_large_token_classifier_hrl_pipeline_xx.md
index b50cc0a119e8ce..33c74c86cfb92d 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-xlm_roberta_large_token_classifier_hrl_pipeline_xx.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-xlm_roberta_large_token_classifier_hrl_pipeline_xx.md
@@ -32,21 +32,7 @@ This pretrained pipeline is built on the top of [xlm_roberta_large_token_classif
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-pipeline = PretrainedPipeline("xlm_roberta_large_token_classifier_hrl_pipeline", lang = "xx")
-
-pipeline.annotate("يمكنكم مشاهدة أمير منطقة الرياض الأمير فيصل بن بندر بن عبد العزيز في كل مناسبة وافتتاح تتعلق بمشاريع التعليم والصحة وخدمة الطرق والمشاريع الثقافية في منطقة الرياض.")
-```
-```scala
-
-val pipeline = new PretrainedPipeline("xlm_roberta_large_token_classifier_hrl_pipeline", lang = "xx")
-pipeline.annotate("يمكنكم مشاهدة أمير منطقة الرياض الأمير فيصل بن بندر بن عبد العزيز في كل مناسبة وافتتاح تتعلق بمشاريع التعليم والصحة وخدمة الطرق والمشاريع الثقافية في منطقة الرياض.")
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-22-xlm_roberta_large_token_classifier_masakhaner_pipeline_xx.md b/docs/_posts/ahmedlone127/2023-05-22-xlm_roberta_large_token_classifier_masakhaner_pipeline_xx.md
index 33594be3b84966..a0a6092a8e4336 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-xlm_roberta_large_token_classifier_masakhaner_pipeline_xx.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-xlm_roberta_large_token_classifier_masakhaner_pipeline_xx.md
@@ -32,21 +32,7 @@ This pretrained pipeline is built on [xlm_roberta_large_token_classifier_masakha
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-masakhaner_pipeline = PretrainedPipeline("xlm_roberta_large_token_classifier_masakhaner_pipeline", lang = "xx")
-
-masakhaner_pipeline.annotate("አህመድ ቫንዳ ከ3-10-2000 ጀምሮ በአዲስ አበባ ኖሯል።")
-```
-```scala
-
-val masakhaner_pipeline = new PretrainedPipeline("xlm_roberta_large_token_classifier_masakhaner_pipeline", lang = "xx")
-val masakhaner_pipeline.annotate("አህመድ ቫንዳ ከ3-10-2000 ጀምሮ በአዲስ አበባ ኖሯል።")
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-22-xlnet_base_token_classifier_conll03_pipeline_en.md b/docs/_posts/ahmedlone127/2023-05-22-xlnet_base_token_classifier_conll03_pipeline_en.md
index e11013676e7752..9395b9b0450103 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-xlnet_base_token_classifier_conll03_pipeline_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-xlnet_base_token_classifier_conll03_pipeline_en.md
@@ -32,23 +32,7 @@ This pretrained pipeline is built on the top of [xlnet_base_token_classifier_con
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-
-pipeline = PretrainedPipeline("xlnet_base_token_classifier_conll03_pipeline", lang = "en")
-
-pipeline.annotate("My name is John and I work at John Snow Labs.")
-```
-```scala
-
-
-val pipeline = new PretrainedPipeline("xlnet_base_token_classifier_conll03_pipeline", lang = "en")
-pipeline.annotate("My name is John and I work at John Snow Labs.")
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-22-xlnet_large_token_classifier_conll03_pipeline_en.md b/docs/_posts/ahmedlone127/2023-05-22-xlnet_large_token_classifier_conll03_pipeline_en.md
index 58dc4fccd0d7f8..b4f98b17e2fbc3 100644
--- a/docs/_posts/ahmedlone127/2023-05-22-xlnet_large_token_classifier_conll03_pipeline_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-22-xlnet_large_token_classifier_conll03_pipeline_en.md
@@ -32,23 +32,7 @@ This pretrained pipeline is built on the top of [xlnet_large_token_classifier_co
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-
-pipeline = PretrainedPipeline("xlnet_large_token_classifier_conll03_pipeline", lang = "en")
-
-pipeline.annotate("My name is John and I work at John Snow Labs.")
-```
-```scala
-
-
-val pipeline = new PretrainedPipeline("xlnet_large_token_classifier_conll03_pipeline", lang = "en")
-pipeline.annotate("My name is John and I work at John Snow Labs.")
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-24-analyze_sentiment_en.md b/docs/_posts/ahmedlone127/2023-05-24-analyze_sentiment_en.md
index 5d9c83df977dbf..4b610cebf162cb 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-analyze_sentiment_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-analyze_sentiment_en.md
@@ -34,39 +34,7 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-
-```python
-
-from sparknlp.pretrained import PretrainedPipeline
-
-pipeline = PretrainedPipeline('analyze_sentiment', lang = 'en')
-
-result = pipeline.fullAnnotate("""Demonicus is a movie turned into a video game! I just love the story and the things that goes on in the film.It is a B-film ofcourse but that doesn`t bother one bit because its made just right and the music was rad! Horror and sword fight freaks,buy this movie now!""")
-
-
-```
-```scala
-
-import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
-val pipeline = new PretrainedPipeline("analyze_sentiment", lang = "en")
-
-val result = pipeline.fullAnnotate("""Demonicus is a movie turned into a video game! I just love the story and the things that goes on in the film.It is a B-film ofcourse but that doesn`t bother one bit because its made just right and the music was rad! Horror and sword fight freaks,buy this movie now!""")
-
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = ["""Demonicus is a movie turned into a video game! I just love the story and the things that goes on in the film.It is a B-film ofcourse but that doesn`t bother one bit because its made just right and the music was rad! Horror and sword fight freaks,buy this movie now!"""]
-result_df = nlu.load('en.classify').predict(text)
-result_df
-
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-24-analyze_sentimentdl_glove_imdb_en.md b/docs/_posts/ahmedlone127/2023-05-24-analyze_sentimentdl_glove_imdb_en.md
index b9f91f44783fce..8f0083c01c486b 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-analyze_sentimentdl_glove_imdb_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-analyze_sentimentdl_glove_imdb_en.md
@@ -34,35 +34,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('analyze_sentimentdl_glove_imdb', lang = 'en')
-annotations = pipeline.fullAnnotate(""Hello from John Snow Labs ! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("analyze_sentimentdl_glove_imdb", lang = "en")
-val result = pipeline.fullAnnotate("Hello from John Snow Labs ! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hello from John Snow Labs ! ""]
-result_df = nlu.load('en.sentiment.glove').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-clean_pattern_en.md b/docs/_posts/ahmedlone127/2023-05-24-clean_pattern_en.md
index b13244944aa964..7b07fd0486dbd5 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-clean_pattern_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-clean_pattern_en.md
@@ -34,33 +34,7 @@ The clean_pattern is a pretrained pipeline that we can use to process text with
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('clean_pattern', lang = 'en')
-annotations = pipeline.fullAnnotate(""Hello from John Snow Labs ! "")[0]
-annotations.keys()
-```
-```scala
-
-
-val pipeline = new PretrainedPipeline("clean_pattern", lang = "en")
-val result = pipeline.fullAnnotate("Hello from John Snow Labs ! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hello from John Snow Labs ! ""]
-result_df = nlu.load('en.clean.pattern').predict(text)
-result_df
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-24-clean_stop_en.md b/docs/_posts/ahmedlone127/2023-05-24-clean_stop_en.md
index 6068e038ad1ee6..0226561f3acd94 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-clean_stop_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-clean_stop_en.md
@@ -34,35 +34,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('clean_stop', lang = 'en')
-annotations = pipeline.fullAnnotate(""Hello from John Snow Labs ! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("clean_stop", lang = "en")
-val result = pipeline.fullAnnotate("Hello from John Snow Labs ! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hello from John Snow Labs ! ""]
-result_df = nlu.load('en.clean.stop').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_de.md b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_de.md
index dd930bea9c5bf6..c4b97d494b207f 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_de.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_de.md
@@ -34,35 +34,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('entity_recognizer_lg', lang = 'de')
-annotations = pipeline.fullAnnotate(""Hallo aus John Snow Labs! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("entity_recognizer_lg", lang = "de")
-val result = pipeline.fullAnnotate("Hallo aus John Snow Labs! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hallo aus John Snow Labs! ""]
-result_df = nlu.load('de.ner.recognizer.lg').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_es.md b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_es.md
index 51c2508bf37b4e..855f0fed257afa 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_es.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_es.md
@@ -33,25 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-from sparknlp.pretrained import PretrainedPipeline
-pipeline = PretrainedPipeline("entity_recognizer_lg", "es")
-
-result = pipeline.annotate("""I love johnsnowlabs! """)
-```
-
-{:.nlu-block}
-```python
-import nlu
-nlu.load("es.ner.lg").predict("""I love johnsnowlabs! """)
-```
-
-
-
{:.model-param}
diff --git a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_fr.md b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_fr.md
index 18c3447a08a0bc..c2d22843e89cba 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_fr.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_fr.md
@@ -34,35 +34,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('entity_recognizer_lg', lang = 'fr')
-annotations = pipeline.fullAnnotate(""Bonjour de John Snow Labs! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("entity_recognizer_lg", lang = "fr")
-val result = pipeline.fullAnnotate("Bonjour de John Snow Labs! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Bonjour de John Snow Labs! ""]
-result_df = nlu.load('fr.ner').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_nl.md b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_nl.md
index 2c911b74026429..31f27d1708a88c 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_nl.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_nl.md
@@ -33,25 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-from sparknlp.pretrained import PretrainedPipeline
-pipeline = PretrainedPipeline("entity_recognizer_lg", "nl")
-
-result = pipeline.annotate("""I love johnsnowlabs! """)
-```
-
-{:.nlu-block}
-```python
-import nlu
-nlu.load("nl.ner.lg").predict("""I love johnsnowlabs! """)
-```
-
-
-
{:.model-param}
diff --git a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_no.md b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_no.md
index 4cefe051b56add..c8b7aab8a11595 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_no.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_no.md
@@ -33,25 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-from sparknlp.pretrained import PretrainedPipeline
-pipeline = PretrainedPipeline("entity_recognizer_lg", "no")
-
-result = pipeline.annotate("""I love johnsnowlabs! """)
-```
-
-{:.nlu-block}
-```python
-import nlu
-nlu.load("no.ner.lg").predict("""I love johnsnowlabs! """)
-```
-
-
-
{:.model-param}
diff --git a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_pl.md b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_pl.md
index 2955701471bfe1..193f16302af83e 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_pl.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_pl.md
@@ -33,25 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-from sparknlp.pretrained import PretrainedPipeline
-pipeline = PretrainedPipeline("entity_recognizer_lg", "pl")
-
-result = pipeline.annotate("""I love johnsnowlabs! """)
-```
-
-{:.nlu-block}
-```python
-import nlu
-nlu.load("pl.ner.lg").predict("""I love johnsnowlabs! """)
-```
-
-
-
{:.model-param}
diff --git a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_pt.md b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_pt.md
index 4b1cde8456ac3c..6a5dc77670e5b3 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_pt.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_pt.md
@@ -33,25 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-from sparknlp.pretrained import PretrainedPipeline
-pipeline = PretrainedPipeline("entity_recognizer_lg", "pt")
-
-result = pipeline.annotate("""I love johnsnowlabs! """)
-```
-
-{:.nlu-block}
-```python
-import nlu
-nlu.load("pt.ner.lg").predict("""I love johnsnowlabs! """)
-```
-
-
-
{:.model-param}
diff --git a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_ru.md b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_ru.md
index 49dfad88bac238..066285352e686c 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_ru.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_ru.md
@@ -33,25 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-from sparknlp.pretrained import PretrainedPipeline
-pipeline = PretrainedPipeline("entity_recognizer_lg", "ru")
-
-result = pipeline.annotate("""I love johnsnowlabs! """)
-```
-
-{:.nlu-block}
-```python
-import nlu
-nlu.load("ru.ner.lg").predict("""I love johnsnowlabs! """)
-```
-
-
-
{:.model-param}
diff --git a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_sv.md b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_sv.md
index 2d7712cc130eec..7fdb92324adfbb 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_sv.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_lg_sv.md
@@ -33,25 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-from sparknlp.pretrained import PretrainedPipeline
-pipeline = PretrainedPipeline("entity_recognizer_lg", "sv")
-
-result = pipeline.annotate("""I love johnsnowlabs! """)
-```
-
-{:.nlu-block}
-```python
-import nlu
-nlu.load("sv.ner.lg").predict("""I love johnsnowlabs! """)
-```
-
-
-
{:.model-param}
diff --git a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_md_de.md b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_md_de.md
index 2598aa24330417..e0413a8449c2a1 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_md_de.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_md_de.md
@@ -33,35 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('entity_recognizer_md', lang = 'de')
-annotations = pipeline.fullAnnotate(""Hallo aus John Snow Labs! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("entity_recognizer_md", lang = "de")
-val result = pipeline.fullAnnotate("Hallo aus John Snow Labs! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hallo aus John Snow Labs! ""]
-result_df = nlu.load('de.ner.recognizer').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_md_es.md b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_md_es.md
index 16fc2ffd0cc20b..f5d3feb29f7b90 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_md_es.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_md_es.md
@@ -33,35 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('entity_recognizer_md', lang = 'es')
-annotations = pipeline.fullAnnotate(""Hola de John Snow Labs! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("entity_recognizer_md", lang = "es")
-val result = pipeline.fullAnnotate("Hola de John Snow Labs! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hola de John Snow Labs! ""]
-result_df = nlu.load('es.ner.md').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_md_fr.md b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_md_fr.md
index 72dac1583e9b59..6a8542f87337dd 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_md_fr.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_md_fr.md
@@ -33,35 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('entity_recognizer_md', lang = 'fr')
-annotations = pipeline.fullAnnotate(""Bonjour de John Snow Labs! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("entity_recognizer_md", lang = "fr")
-val result = pipeline.fullAnnotate("Bonjour de John Snow Labs! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Bonjour de John Snow Labs! ""]
-result_df = nlu.load('fr.ner.md').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_md_no.md b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_md_no.md
index 5e43ac4f67f878..d83b24fdd46076 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_md_no.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_md_no.md
@@ -33,35 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('entity_recognizer_md', lang = 'no')
-annotations = pipeline.fullAnnotate(""Hei fra John Snow Labs! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("entity_recognizer_md", lang = "no")
-val result = pipeline.fullAnnotate("Hei fra John Snow Labs! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hei fra John Snow Labs! ""]
-result_df = nlu.load('no.ner.md').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_md_ru.md b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_md_ru.md
index daa6bd25d17025..ef852e7b641b21 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_md_ru.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_md_ru.md
@@ -33,35 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('entity_recognizer_md', lang = 'ru')
-annotations = pipeline.fullAnnotate(""Здравствуйте из Джона Снежных Лабораторий! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("entity_recognizer_md", lang = "ru")
-val result = pipeline.fullAnnotate("Здравствуйте из Джона Снежных Лабораторий! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Здравствуйте из Джона Снежных Лабораторий! ""]
-result_df = nlu.load('ru.ner.md').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_md_sv.md b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_md_sv.md
index e2153d5b120cfc..372841e0a9dd29 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_md_sv.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_md_sv.md
@@ -33,35 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('entity_recognizer_md', lang = 'sv')
-annotations = pipeline.fullAnnotate(""Hej från John Snow Labs! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("entity_recognizer_md", lang = "sv")
-val result = pipeline.fullAnnotate("Hej från John Snow Labs! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hej från John Snow Labs! ""]
-result_df = nlu.load('sv.ner.md').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_sm_es.md b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_sm_es.md
index 53cfb3b430866a..525acf5f72da3f 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_sm_es.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_sm_es.md
@@ -33,35 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('entity_recognizer_sm', lang = 'es')
-annotations = pipeline.fullAnnotate(""Hola de John Snow Labs! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("entity_recognizer_sm", lang = "es")
-val result = pipeline.fullAnnotate("Hola de John Snow Labs! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hola de John Snow Labs! ""]
-result_df = nlu.load('es.ner').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_sm_no.md b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_sm_no.md
index 37a8591fe2ef78..b0ae7737cb368f 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_sm_no.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_sm_no.md
@@ -33,35 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('entity_recognizer_sm', lang = 'no')
-annotations = pipeline.fullAnnotate(""Hei fra John Snow Labs! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("entity_recognizer_sm", lang = "no")
-val result = pipeline.fullAnnotate("Hei fra John Snow Labs! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hei fra John Snow Labs! ""]
-result_df = nlu.load('no.ner').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_sm_ru.md b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_sm_ru.md
index 6ae2893777183f..5705b7a501cb86 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_sm_ru.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_sm_ru.md
@@ -33,35 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('entity_recognizer_sm', lang = 'ru')
-annotations = pipeline.fullAnnotate(""Здравствуйте из Джона Снежных Лабораторий! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("entity_recognizer_sm", lang = "ru")
-val result = pipeline.fullAnnotate("Здравствуйте из Джона Снежных Лабораторий! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Здравствуйте из Джона Снежных Лабораторий! ""]
-result_df = nlu.load('ru.ner').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_sm_sv.md b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_sm_sv.md
index f7642a41d11171..bb3360f31b314b 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_sm_sv.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-entity_recognizer_sm_sv.md
@@ -33,35 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('entity_recognizer_sm', lang = 'sv')
-annotations = pipeline.fullAnnotate(""Hej från John Snow Labs! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("entity_recognizer_sm", lang = "sv")
-val result = pipeline.fullAnnotate("Hej från John Snow Labs! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hej från John Snow Labs! ""]
-result_df = nlu.load('sv.ner').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-explain_document_dl_en.md b/docs/_posts/ahmedlone127/2023-05-24-explain_document_dl_en.md
index ce04a272f78d0b..373095bcd9ae01 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-explain_document_dl_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-explain_document_dl_en.md
@@ -34,35 +34,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipeline
-pipeline = PretrainedPipeline('explain_document_dl', lang = 'en')
-annotations = pipeline.fullAnnotate("The Mona Lisa is an oil painting from the 16th century.")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("explain_document_dl", lang = "en")
-val result = pipeline.fullAnnotate("The Mona Lisa is an oil painting from the 16th century.")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = ["The Mona Lisa is an oil painting from the 16th century."]
-result_df = nlu.load('en.explain.dl').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-explain_document_lg_es.md b/docs/_posts/ahmedlone127/2023-05-24-explain_document_lg_es.md
index 81358c6d035804..2ca4a444df90ba 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-explain_document_lg_es.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-explain_document_lg_es.md
@@ -34,35 +34,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('explain_document_lg', lang = 'es')
-annotations = pipeline.fullAnnotate(""Hola de John Snow Labs! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("explain_document_lg", lang = "es")
-val result = pipeline.fullAnnotate("Hola de John Snow Labs! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hola de John Snow Labs! ""]
-result_df = nlu.load('es.explain.lg').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-explain_document_lg_no.md b/docs/_posts/ahmedlone127/2023-05-24-explain_document_lg_no.md
index 9702d232220434..927822969f8122 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-explain_document_lg_no.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-explain_document_lg_no.md
@@ -34,35 +34,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('explain_document_lg', lang = 'no')
-annotations = pipeline.fullAnnotate(""Hei fra John Snow Labs! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("explain_document_lg", lang = "no")
-val result = pipeline.fullAnnotate("Hei fra John Snow Labs! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hei fra John Snow Labs! ""]
-result_df = nlu.load('no.explain.lg').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-explain_document_lg_ru.md b/docs/_posts/ahmedlone127/2023-05-24-explain_document_lg_ru.md
index 9fdae922e46e8a..64c7829a9140f0 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-explain_document_lg_ru.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-explain_document_lg_ru.md
@@ -34,35 +34,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('explain_document_lg', lang = 'ru')
-annotations = pipeline.fullAnnotate(""Здравствуйте из Джона Снежных Лабораторий! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("explain_document_lg", lang = "ru")
-val result = pipeline.fullAnnotate("Здравствуйте из Джона Снежных Лабораторий! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Здравствуйте из Джона Снежных Лабораторий! ""]
-result_df = nlu.load('ru.explain.lg').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-explain_document_lg_sv.md b/docs/_posts/ahmedlone127/2023-05-24-explain_document_lg_sv.md
index 132f8cdbb495a2..147cc6720b1ea2 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-explain_document_lg_sv.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-explain_document_lg_sv.md
@@ -34,35 +34,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('explain_document_lg', lang = 'sv')
-annotations = pipeline.fullAnnotate(""Hej från John Snow Labs! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("explain_document_lg", lang = "sv")
-val result = pipeline.fullAnnotate("Hej från John Snow Labs! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hej från John Snow Labs! ""]
-result_df = nlu.load('sv.explain.lg').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-explain_document_md_de.md b/docs/_posts/ahmedlone127/2023-05-24-explain_document_md_de.md
index 3d4f4dc3ef291d..bf618f14deec66 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-explain_document_md_de.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-explain_document_md_de.md
@@ -33,35 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('explain_document_md', lang = 'de')
-annotations = pipeline.fullAnnotate(""Hallo aus John Snow Labs! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("explain_document_md", lang = "de")
-val result = pipeline.fullAnnotate("Hallo aus John Snow Labs! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hallo aus John Snow Labs! ""]
-result_df = nlu.load('de.explain.document').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-explain_document_md_es.md b/docs/_posts/ahmedlone127/2023-05-24-explain_document_md_es.md
index 0ce6e3cfe83274..0a4b97317d5dc5 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-explain_document_md_es.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-explain_document_md_es.md
@@ -33,35 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('explain_document_md', lang = 'es')
-annotations = pipeline.fullAnnotate(""Hola de John Snow Labs! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("explain_document_md", lang = "es")
-val result = pipeline.fullAnnotate("Hola de John Snow Labs! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hola de John Snow Labs! ""]
-result_df = nlu.load('es.explain.md').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-explain_document_md_fr.md b/docs/_posts/ahmedlone127/2023-05-24-explain_document_md_fr.md
index a43059872d0343..a42c90e8fcb162 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-explain_document_md_fr.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-explain_document_md_fr.md
@@ -33,35 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('explain_document_md', lang = 'fr')
-annotations = pipeline.fullAnnotate(""Bonjour de John Snow Labs! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("explain_document_md", lang = "fr")
-val result = pipeline.fullAnnotate("Bonjour de John Snow Labs! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Bonjour de John Snow Labs! ""]
-result_df = nlu.load('fr.explain.md').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-explain_document_md_no.md b/docs/_posts/ahmedlone127/2023-05-24-explain_document_md_no.md
index d0fc0624d92ee7..722979d39c9881 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-explain_document_md_no.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-explain_document_md_no.md
@@ -33,35 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('explain_document_md', lang = 'no')
-annotations = pipeline.fullAnnotate(""Hei fra John Snow Labs! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("explain_document_md", lang = "no")
-val result = pipeline.fullAnnotate("Hei fra John Snow Labs! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hei fra John Snow Labs! ""]
-result_df = nlu.load('no.explain.md').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-explain_document_md_ru.md b/docs/_posts/ahmedlone127/2023-05-24-explain_document_md_ru.md
index 761bb44e1825bd..d009a4bbde8940 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-explain_document_md_ru.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-explain_document_md_ru.md
@@ -33,35 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('explain_document_md', lang = 'ru')
-annotations = pipeline.fullAnnotate(""Здравствуйте из Джона Снежных Лабораторий! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("explain_document_md", lang = "ru")
-val result = pipeline.fullAnnotate("Здравствуйте из Джона Снежных Лабораторий! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Здравствуйте из Джона Снежных Лабораторий! ""]
-result_df = nlu.load('ru.explain.md').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-explain_document_md_sv.md b/docs/_posts/ahmedlone127/2023-05-24-explain_document_md_sv.md
index 395727eadff20a..2e3085c84f1d20 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-explain_document_md_sv.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-explain_document_md_sv.md
@@ -33,35 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('explain_document_md', lang = 'sv')
-annotations = pipeline.fullAnnotate(""Hej från John Snow Labs! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("explain_document_md", lang = "sv")
-val result = pipeline.fullAnnotate("Hej från John Snow Labs! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hej från John Snow Labs! ""]
-result_df = nlu.load('sv.explain.md').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-explain_document_ml_en.md b/docs/_posts/ahmedlone127/2023-05-24-explain_document_ml_en.md
index c8c470caefcf24..4261fe36617030 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-explain_document_ml_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-explain_document_ml_en.md
@@ -34,33 +34,7 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-
-from sparknlp.pretrained import PretrainedPipeline
-pipeline = PretrainedPipeline('explain_document_ml', lang = 'en')
-annotations = pipeline.fullAnnotate(""Hello from John Snow Labs ! "")[0]
-annotations.keys()
-```
-```scala
-
-
-val pipeline = new PretrainedPipeline("explain_document_ml", lang = "en")
-val result = pipeline.fullAnnotate("Hello from John Snow Labs ! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hello from John Snow Labs ! ""]
-result_df = nlu.load('en.explain').predict(text)
-result_df
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-24-explain_document_sm_es.md b/docs/_posts/ahmedlone127/2023-05-24-explain_document_sm_es.md
index edcce5d9a5a792..95b955ce51bcfb 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-explain_document_sm_es.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-explain_document_sm_es.md
@@ -33,35 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('explain_document_sm', lang = 'es')
-annotations = pipeline.fullAnnotate(""Hola de John Snow Labs! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("explain_document_sm", lang = "es")
-val result = pipeline.fullAnnotate("Hola de John Snow Labs! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hola de John Snow Labs! ""]
-result_df = nlu.load('es.explain').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-explain_document_sm_no.md b/docs/_posts/ahmedlone127/2023-05-24-explain_document_sm_no.md
index 52a43cf866c269..6b300ca302d561 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-explain_document_sm_no.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-explain_document_sm_no.md
@@ -33,35 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('explain_document_sm', lang = 'no')
-annotations = pipeline.fullAnnotate(""Hei fra John Snow Labs! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("explain_document_sm", lang = "no")
-val result = pipeline.fullAnnotate("Hei fra John Snow Labs! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hei fra John Snow Labs! ""]
-result_df = nlu.load('no.explain').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-explain_document_sm_ru.md b/docs/_posts/ahmedlone127/2023-05-24-explain_document_sm_ru.md
index 782cc68a2a9e61..b1c0f204de2528 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-explain_document_sm_ru.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-explain_document_sm_ru.md
@@ -33,35 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('explain_document_sm', lang = 'ru')
-annotations = pipeline.fullAnnotate(""Здравствуйте из Джона Снежных Лабораторий! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("explain_document_sm", lang = "ru")
-val result = pipeline.fullAnnotate("Здравствуйте из Джона Снежных Лабораторий! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Здравствуйте из Джона Снежных Лабораторий! ""]
-result_df = nlu.load('ru.explain').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-explain_document_sm_sv.md b/docs/_posts/ahmedlone127/2023-05-24-explain_document_sm_sv.md
index eb558461247667..04a0d72c777ffb 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-explain_document_sm_sv.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-explain_document_sm_sv.md
@@ -33,35 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('explain_document_sm', lang = 'sv')
-annotations = pipeline.fullAnnotate(""Hej från John Snow Labs! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("explain_document_sm", lang = "sv")
-val result = pipeline.fullAnnotate("Hej från John Snow Labs! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hej från John Snow Labs! ""]
-result_df = nlu.load('sv.explain').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-match_chunks_en.md b/docs/_posts/ahmedlone127/2023-05-24-match_chunks_en.md
index bc4e550333f299..27edbcd4dcba6d 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-match_chunks_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-match_chunks_en.md
@@ -32,41 +32,7 @@ The pipeline uses regex `
?/
*
+`
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipeline
-
-pipeline_local = PretrainedPipeline('match_chunks')
-
-result = pipeline_local.annotate("David visited the restaurant yesterday with his family. He also visited and the day before, but at that time he was alone. David again visited today with his colleagues. He and his friends really liked the food and hoped to visit again tomorrow.")
-
-result['chunk']
-```
-```scala
-
-import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline import com.johnsnowlabs.nlp.SparkNLP
-
-SparkNLP.version()
-val testData = spark.createDataFrame(Seq( (1, "David visited the restaurant yesterday with his family. He also visited and the day before, but at that time he was alone. David again visited today with his colleagues. He and his friends really liked the food and hoped to visit again tomorrow."))).toDF("id", "text")
-
-val pipeline = PretrainedPipeline("match_chunks", lang="en")
-
-val annotation = pipeline.transform(testData)
-
-annotation.show()
-```
-
-
-{:.nlu-block}
-```python
-import nlu
-nlu.load("en.match.chunks").predict("""David visited the restaurant yesterday with his family. He also visited and the day before, but at that time he was alone. David again visited today with his colleagues. He and his friends really liked the food and hoped to visit again tomorrow.""")
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-24-match_datetime_en.md b/docs/_posts/ahmedlone127/2023-05-24-match_datetime_en.md
index 14a0f3958959fb..3d4f273132097c 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-match_datetime_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-match_datetime_en.md
@@ -32,35 +32,7 @@ DateMatcher based on yyyy/MM/dd
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-pipeline_local = PretrainedPipeline('match_datetime')
-
-tres = pipeline_local.fullAnnotate(input_list)[0]
-for dte in tres['date']:
- sent = tres['sentence'][int(dte.metadata['sentence'])]
- print (f'text/chunk {sent.result[dte.begin:dte.end+1]} | mapped_date: {dte.result}')
-```
-```scala
-
-import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline import com.johnsnowlabs.nlp.SparkNLP
-SparkNLP.version()
-
-val testData = spark.createDataFrame(Seq( (1, "David visited the restaurant yesterday with his family.
-He also visited and the day before, but at that time he was alone.
-David again visited today with his colleagues.
-He and his friends really liked the food and hoped to visit again tomorrow."))).toDF("id", "text")
-
-val pipeline = PretrainedPipeline("match_datetime", lang="en")
-
-val annotation = pipeline.transform(testData)
-
-annotation.show()
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-24-match_pattern_en.md b/docs/_posts/ahmedlone127/2023-05-24-match_pattern_en.md
index f6664a3ddd1cb7..05e23273179e6b 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-match_pattern_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-match_pattern_en.md
@@ -33,16 +33,7 @@ The match_pattern is a pretrained pipeline that we can use to process text with
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-from sparknlp.pretrained import PretrainedPipeline
-pipeline = PretrainedPipeline("match_pattern", "en", "clinical/models")
- result = pipeline.annotate("""I love johnsnowlabs! """)
-```
-
-
{:.model-param}
diff --git a/docs/_posts/ahmedlone127/2023-05-24-movies_sentiment_analysis_en.md b/docs/_posts/ahmedlone127/2023-05-24-movies_sentiment_analysis_en.md
index ffc88a8a21c0af..1e277044f1530a 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-movies_sentiment_analysis_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-movies_sentiment_analysis_en.md
@@ -33,16 +33,7 @@ The movies_sentiment_analysis is a pretrained pipeline that we can use to proces
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-from sparknlp.pretrained import PretrainedPipeline
-pipeline = PretrainedPipeline("movies_sentiment_analysis", "en")
-result = pipeline.annotate("""I love johnsnowlabs! """)
-```
-
-
{:.model-param}
diff --git a/docs/_posts/ahmedlone127/2023-05-24-onto_recognize_entities_lg_en.md b/docs/_posts/ahmedlone127/2023-05-24-onto_recognize_entities_lg_en.md
index c53073ddb80d2f..b2d21a19e91baa 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-onto_recognize_entities_lg_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-onto_recognize_entities_lg_en.md
@@ -33,25 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-from sparknlp.pretrained import PretrainedPipeline
-pipeline = PretrainedPipeline("onto_recognize_entities_lg", "en")
-
-result = pipeline.annotate("""I love johnsnowlabs! """)
-```
-
-{:.nlu-block}
-```python
-import nlu
-nlu.load("en.ner.onto.lg").predict("""I love johnsnowlabs! """)
-```
-
-
-
{:.model-param}
diff --git a/docs/_posts/ahmedlone127/2023-05-24-onto_recognize_entities_sm_en.md b/docs/_posts/ahmedlone127/2023-05-24-onto_recognize_entities_sm_en.md
index 61c9e4f510886b..250716e139ac16 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-onto_recognize_entities_sm_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-onto_recognize_entities_sm_en.md
@@ -33,35 +33,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('onto_recognize_entities_sm', lang = 'en')
-annotations = pipeline.fullAnnotate(""Hello from John Snow Labs ! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("onto_recognize_entities_sm", lang = "en")
-val result = pipeline.fullAnnotate("Hello from John Snow Labs ! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hello from John Snow Labs ! ""]
-result_df = nlu.load('en.ner.onto.sm').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-recognize_entities_bert_en.md b/docs/_posts/ahmedlone127/2023-05-24-recognize_entities_bert_en.md
index b57803f6d35a4e..6b3629ad27c371 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-recognize_entities_bert_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-recognize_entities_bert_en.md
@@ -34,35 +34,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('recognize_entities_bert', lang = 'en')
-annotations = pipeline.fullAnnotate(""Hello from John Snow Labs ! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("recognize_entities_bert", lang = "en")
-val result = pipeline.fullAnnotate("Hello from John Snow Labs ! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hello from John Snow Labs ! ""]
-result_df = nlu.load('en.ner.bert').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-recognize_entities_dl_en.md b/docs/_posts/ahmedlone127/2023-05-24-recognize_entities_dl_en.md
index aad937ec1cdd60..2706b675fcf069 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-recognize_entities_dl_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-recognize_entities_dl_en.md
@@ -34,35 +34,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('recognize_entities_dl', lang = 'en')
-annotations = pipeline.fullAnnotate(""Hello from John Snow Labs ! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("recognize_entities_dl", lang = "en")
-val result = pipeline.fullAnnotate("Hello from John Snow Labs ! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hello from John Snow Labs ! ""]
-result_df = nlu.load('en.ner').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-24-text_cleaning_en.md b/docs/_posts/ahmedlone127/2023-05-24-text_cleaning_en.md
index df3850fb08eb8e..1fb49f48f29565 100644
--- a/docs/_posts/ahmedlone127/2023-05-24-text_cleaning_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-24-text_cleaning_en.md
@@ -33,16 +33,7 @@ The text_cleaning is a pretrained pipeline that we can use to process text with
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-from sparknlp.pretrained import PretrainedPipeline
-pipeline = PretrainedPipeline("text_cleaning", "en")
-result = pipeline.annotate("""I love johnsnowlabs! """)
-```
-
-
{:.model-param}
diff --git a/docs/_posts/ahmedlone127/2023-05-25-albert_base_token_classifier_conll03_pipeline_en.md b/docs/_posts/ahmedlone127/2023-05-25-albert_base_token_classifier_conll03_pipeline_en.md
index e2e1cc820d93d9..1a614340b5e4f1 100644
--- a/docs/_posts/ahmedlone127/2023-05-25-albert_base_token_classifier_conll03_pipeline_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-25-albert_base_token_classifier_conll03_pipeline_en.md
@@ -32,23 +32,7 @@ This pretrained pipeline is built on the top of [albert_base_token_classifier_co
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-
-pipeline = PretrainedPipeline("albert_base_token_classifier_conll03_pipeline", lang = "en")
-
-pipeline.annotate("My name is John and I work at John Snow Labs.")
-```
-```scala
-
-
-val pipeline = new PretrainedPipeline("albert_base_token_classifier_conll03_pipeline", lang = "en")
-pipeline.annotate("My name is John and I work at John Snow Labs."))
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-25-albert_large_token_classifier_conll03_pipeline_en.md b/docs/_posts/ahmedlone127/2023-05-25-albert_large_token_classifier_conll03_pipeline_en.md
index 8e78af9a31809a..218612f0a2d072 100644
--- a/docs/_posts/ahmedlone127/2023-05-25-albert_large_token_classifier_conll03_pipeline_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-25-albert_large_token_classifier_conll03_pipeline_en.md
@@ -32,23 +32,7 @@ This pretrained pipeline is built on the top of [albert_large_token_classifier_c
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-
-pipeline = PretrainedPipeline("albert_large_token_classifier_conll03_pipeline", lang = "en")
-
-pipeline.annotate("My name is John and I work at John Snow Labs.")
-```
-```scala
-
-
-val pipeline = new PretrainedPipeline("albert_large_token_classifier_conll03_pipeline", lang = "en")
-pipeline.annotate("My name is John and I work at John Snow Labs."))
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-25-albert_xlarge_token_classifier_conll03_pipeline_en.md b/docs/_posts/ahmedlone127/2023-05-25-albert_xlarge_token_classifier_conll03_pipeline_en.md
index 4ae7fcc69bac01..4a76a5ffdcb430 100644
--- a/docs/_posts/ahmedlone127/2023-05-25-albert_xlarge_token_classifier_conll03_pipeline_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-25-albert_xlarge_token_classifier_conll03_pipeline_en.md
@@ -32,23 +32,7 @@ This pretrained pipeline is built on the top of [albert_xlarge_token_classifier_
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-
-pipeline = PretrainedPipeline("albert_xlarge_token_classifier_conll03_pipeline", lang = "en")
-
-pipeline.annotate("My name is John and I work at John Snow Labs.")
-```
-```scala
-
-
-val pipeline = new PretrainedPipeline("albert_xlarge_token_classifier_conll03_pipeline", lang = "en")
-pipeline.annotate("My name is John and I work at John Snow Labs."))
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-25-analyze_sentiment_en.md b/docs/_posts/ahmedlone127/2023-05-25-analyze_sentiment_en.md
index 8bdc4ac6e9d31a..0772d9c28e4f1c 100644
--- a/docs/_posts/ahmedlone127/2023-05-25-analyze_sentiment_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-25-analyze_sentiment_en.md
@@ -34,39 +34,7 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-
-```python
-
-from sparknlp.pretrained import PretrainedPipeline
-
-pipeline = PretrainedPipeline('analyze_sentiment', lang = 'en')
-
-result = pipeline.fullAnnotate("""Demonicus is a movie turned into a video game! I just love the story and the things that goes on in the film.It is a B-film ofcourse but that doesn`t bother one bit because its made just right and the music was rad! Horror and sword fight freaks,buy this movie now!""")
-
-
-```
-```scala
-
-import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
-val pipeline = new PretrainedPipeline("analyze_sentiment", lang = "en")
-
-val result = pipeline.fullAnnotate("""Demonicus is a movie turned into a video game! I just love the story and the things that goes on in the film.It is a B-film ofcourse but that doesn`t bother one bit because its made just right and the music was rad! Horror and sword fight freaks,buy this movie now!""")
-
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = ["""Demonicus is a movie turned into a video game! I just love the story and the things that goes on in the film.It is a B-film ofcourse but that doesn`t bother one bit because its made just right and the music was rad! Horror and sword fight freaks,buy this movie now!"""]
-result_df = nlu.load('en.classify').predict(text)
-result_df
-
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-25-analyze_sentimentdl_glove_imdb_en.md b/docs/_posts/ahmedlone127/2023-05-25-analyze_sentimentdl_glove_imdb_en.md
index 2706b7b2ff19b3..161023da722d18 100644
--- a/docs/_posts/ahmedlone127/2023-05-25-analyze_sentimentdl_glove_imdb_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-25-analyze_sentimentdl_glove_imdb_en.md
@@ -34,35 +34,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('analyze_sentimentdl_glove_imdb', lang = 'en')
-annotations = pipeline.fullAnnotate(""Hello from John Snow Labs ! "")[0]
-annotations.keys()
-
-```
-```scala
-
-val pipeline = new PretrainedPipeline("analyze_sentimentdl_glove_imdb", lang = "en")
-val result = pipeline.fullAnnotate("Hello from John Snow Labs ! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hello from John Snow Labs ! ""]
-result_df = nlu.load('en.sentiment.glove').predict(text)
-result_df
-
-```
-
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
```python
diff --git a/docs/_posts/ahmedlone127/2023-05-25-bert_sequence_classifier_age_news_pipeline_en.md b/docs/_posts/ahmedlone127/2023-05-25-bert_sequence_classifier_age_news_pipeline_en.md
index e58bd487c8d55e..e261c7c911c9e2 100644
--- a/docs/_posts/ahmedlone127/2023-05-25-bert_sequence_classifier_age_news_pipeline_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-25-bert_sequence_classifier_age_news_pipeline_en.md
@@ -32,23 +32,7 @@ This pretrained pipeline is built on the top of [bert_sequence_classifier_age_ne
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-
-news_pipeline = PretrainedPipeline("bert_sequence_classifier_age_news_pipeline", lang = "en")
-
-news_pipeline.annotate("Microsoft has taken its first step into the metaverse.")
-```
-```scala
-
-
-val news_pipeline = new PretrainedPipeline("bert_sequence_classifier_age_news_pipeline", lang = "en")
-news_pipeline.annotate("Microsoft has taken its first step into the metaverse.")
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-25-bert_sequence_classifier_trec_coarse_pipeline_en.md b/docs/_posts/ahmedlone127/2023-05-25-bert_sequence_classifier_trec_coarse_pipeline_en.md
index a60580df832493..3bebd8be5a253a 100644
--- a/docs/_posts/ahmedlone127/2023-05-25-bert_sequence_classifier_trec_coarse_pipeline_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-25-bert_sequence_classifier_trec_coarse_pipeline_en.md
@@ -34,23 +34,7 @@ The TREC dataset for question classification consists of open-domain, fact-based
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-
-trec_pipeline = PretrainedPipeline("bert_sequence_classifier_trec_coarse_pipeline", lang = "en")
-
-trec_pipeline.annotate("Germany is the largest country in Europe economically.")
-```
-```scala
-
-
-val trec_pipeline = new PretrainedPipeline("bert_sequence_classifier_trec_coarse_pipeline", lang = "en")
-trec_pipeline.annotate("Germany is the largest country in Europe economically.")
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-25-bert_token_classifier_dutch_udlassy_ner_pipeline_nl.md b/docs/_posts/ahmedlone127/2023-05-25-bert_token_classifier_dutch_udlassy_ner_pipeline_nl.md
index 334a754c8aadbe..0a5d83e6f0cc16 100644
--- a/docs/_posts/ahmedlone127/2023-05-25-bert_token_classifier_dutch_udlassy_ner_pipeline_nl.md
+++ b/docs/_posts/ahmedlone127/2023-05-25-bert_token_classifier_dutch_udlassy_ner_pipeline_nl.md
@@ -32,21 +32,7 @@ This pretrained pipeline is built on the top of [bert_token_classifier_dutch_udl
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-pipeline = PretrainedPipeline("bert_token_classifier_dutch_udlassy_ner_pipeline", lang = "nl")
-
-pipeline.annotate("Mijn naam is Peter Fergusson. Ik woon sinds oktober 2011 in New York en werk 5 jaar bij Tesla Motor.")
-```
-```scala
-
-val pipeline = new PretrainedPipeline("bert_token_classifier_dutch_udlassy_ner_pipeline", lang = "nl")
-pipeline.annotate("Mijn naam is Peter Fergusson. Ik woon sinds oktober 2011 in New York en werk 5 jaar bij Tesla Motor.")
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-25-bert_token_classifier_hi_en_ner_pipeline_hi.md b/docs/_posts/ahmedlone127/2023-05-25-bert_token_classifier_hi_en_ner_pipeline_hi.md
index cec6fc28e13e46..9658e818519183 100644
--- a/docs/_posts/ahmedlone127/2023-05-25-bert_token_classifier_hi_en_ner_pipeline_hi.md
+++ b/docs/_posts/ahmedlone127/2023-05-25-bert_token_classifier_hi_en_ner_pipeline_hi.md
@@ -32,21 +32,7 @@ This pretrained pipeline is built on [bert_token_classifier_hi_en_ner](https://n
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-pipeline = PretrainedPipeline("bert_token_classifier_hi_en_ner_pipeline", lang = "hi")
-
-pipeline.annotate("रिलायंस इंडस्ट्रीज़ लिमिटेड (Reliance Industries Limited) एक भारतीय संगुटिका नियंत्रक कंपनी है, जिसका मुख्यालय मुंबई, महाराष्ट्र (Maharashtra) में स्थित है।रतन नवल टाटा (28 दिसंबर 1937, को मुम्बई (Mumbai), में जन्मे) टाटा समुह के वर्तमान अध्यक्ष, जो भारत की सबसे बड़ी व्यापारिक समूह है, जिसकी स्थापना जमशेदजी टाटा ने की और उनके परिवार की पीढियों ने इसका विस्तार किया और इसे दृढ़ बनाया।")
-```
-```scala
-
-val pipeline = new PretrainedPipeline("bert_token_classifier_hi_en_ner_pipeline", lang = "hi")
-val pipeline.annotate("रिलायंस इंडस्ट्रीज़ लिमिटेड (Reliance Industries Limited) एक भारतीय संगुटिका नियंत्रक कंपनी है, जिसका मुख्यालय मुंबई, महाराष्ट्र (Maharashtra) में स्थित है।रतन नवल टाटा (28 दिसंबर 1937, को मुम्बई (Mumbai), में जन्मे) टाटा समुह के वर्तमान अध्यक्ष, जो भारत की सबसे बड़ी व्यापारिक समूह है, जिसकी स्थापना जमशेदजी टाटा ने की और उनके परिवार की पीढियों ने इसका विस्तार किया और इसे दृढ़ बनाया।")
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-25-bert_token_classifier_scandi_ner_pipeline_xx.md b/docs/_posts/ahmedlone127/2023-05-25-bert_token_classifier_scandi_ner_pipeline_xx.md
index 1d374a3449d63e..d62223e03a0a82 100644
--- a/docs/_posts/ahmedlone127/2023-05-25-bert_token_classifier_scandi_ner_pipeline_xx.md
+++ b/docs/_posts/ahmedlone127/2023-05-25-bert_token_classifier_scandi_ner_pipeline_xx.md
@@ -32,20 +32,7 @@ This pretrained pipeline is built on [bert_token_classifier_scandi_ner](https://
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-scandiner_pipeline = PretrainedPipeline("bert_token_classifier_scandi_ner_pipeline", lang = "xx")
-scandiner_pipeline.annotate("Hans er professor ved Statens Universitet, som ligger i København, og han er en rigtig københavner.")
-```
-```scala
-
-val scandiner_pipeline = new PretrainedPipeline("bert_token_classifier_scandi_ner_pipeline", lang = "xx")
-
-val scandiner_pipeline.annotate("Hans er professor ved Statens Universitet, som ligger i København, og han er en rigtig københavner.")
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-25-clean_pattern_en.md b/docs/_posts/ahmedlone127/2023-05-25-clean_pattern_en.md
index f8f32369a4eda7..3792288064faae 100644
--- a/docs/_posts/ahmedlone127/2023-05-25-clean_pattern_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-25-clean_pattern_en.md
@@ -34,33 +34,7 @@ The clean_pattern is a pretrained pipeline that we can use to process text with
## How to use
-
-{% include programmingLanguageSelectScalaPythonNLU.html %}
-```python
-
-
-from sparknlp.pretrained import PretrainedPipelinein
-pipeline = PretrainedPipeline('clean_pattern', lang = 'en')
-annotations = pipeline.fullAnnotate(""Hello from John Snow Labs ! "")[0]
-annotations.keys()
-```
-```scala
-
-
-val pipeline = new PretrainedPipeline("clean_pattern", lang = "en")
-val result = pipeline.fullAnnotate("Hello from John Snow Labs ! ")(0)
-```
-
-{:.nlu-block}
-```python
-
-import nlu
-text = [""Hello from John Snow Labs ! ""]
-result_df = nlu.load('en.clean.pattern').predict(text)
-result_df
-```
-
{% include programmingLanguageSelectScalaPythonNLU.html %}
diff --git a/docs/_posts/ahmedlone127/2023-05-25-clean_stop_en.md b/docs/_posts/ahmedlone127/2023-05-25-clean_stop_en.md
index 0f2a945ce528cf..23a7966fc4f16d 100644
--- a/docs/_posts/ahmedlone127/2023-05-25-clean_stop_en.md
+++ b/docs/_posts/ahmedlone127/2023-05-25-clean_stop_en.md
@@ -34,35 +34,8 @@ It performs most of the common text processing tasks on your dataframe
## How to use
-