Add model 2023-05-27-entity_recognizer_md_no

docs/_posts/ahmedlone127/2023-05-27-entity_recognizer_md_no.md

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+---
+layout: model
+title: Recognize Entities DL Pipeline for Norwegian (Bokmal) - Medium
+author: John Snow Labs
+name: entity_recognizer_md
+date: 2023-05-27
+tags: [open_source, norwegian_bokmal, entity_recognizer_md, pipeline, "no"]
+task: Named Entity Recognition
+language: "no"
+edition: Spark NLP 4.4.2
+spark_version: 3.2
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+The entity_recognizer_md is a pretrained pipeline that we can use to process text with a simple pipeline that performs basic processing steps.
+It performs most of the common text processing tasks on your dataframe
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/entity_recognizer_md_no_4.4.2_3.2_1685197418614.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/entity_recognizer_md_no_4.4.2_3.2_1685197418614.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+<div class="tabs-box" markdown="1">
+{% 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
+
+```
+</div>
+
+<div class="tabs-box" markdown="1">
+{% 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
+```
+</div>
+
+## Results
+
+```bash
+Results
+
+
+|    | document                     | sentence                    | token                                   | embeddings                   | ner                                   | entities            |
+|---:|:-----------------------------|:----------------------------|:----------------------------------------|:-----------------------------|:--------------------------------------|:--------------------|
+|  0 | ['Hei fra John Snow Labs! '] | ['Hei fra John Snow Labs!'] | ['Hei', 'fra', 'John', 'Snow', 'Labs!'] | [[0.1868100017309188,.,...]] | ['O', 'O', 'B-PER', 'I-PER', 'I-PER'] | ['John Snow Labs!'] |
+
+
+{:.model-param}
+```
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|entity_recognizer_md|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 4.4.2+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|no|
+|Size:|462.8 MB|
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetector
+- TokenizerModel
+- WordEmbeddingsModel
+- NerDLModel
+- NerConverter