Add model 2023-05-25-onto_recognize_entities_bert_mini_en

docs/_posts/ahmedlone127/2023-05-25-onto_recognize_entities_bert_mini_en.md

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+---
+layout: model
+title: Recognize Entities OntoNotes pipeline - BERT Mini
+author: John Snow Labs
+name: onto_recognize_entities_bert_mini
+date: 2023-05-25
+tags: [open_source, english, onto_recognize_entities_bert_mini, pipeline, en]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 4.4.2
+spark_version: 3.4
+supported: true
+annotator: PipelineModel
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+The onto_recognize_entities_bert_mini is a pretrained pipeline that we can use to process text with a simple pipeline that performs basic processing steps 
+and recognizes entities .
+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/onto_recognize_entities_bert_mini_en_4.4.2_3.4_1685003078331.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/onto_recognize_entities_bert_mini_en_4.4.2_3.4_1685003078331.zip){:.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('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
+
+```
+</div>
+
+<div class="tabs-box" markdown="1">
+{% 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
+```
+</div>
+
+## Results
+
+```bash
+Results
+
+
+|    | document                         | sentence                        | token                                          | embeddings                   | ner                                        | entities           |
+|---:|:---------------------------------|:--------------------------------|:-----------------------------------------------|:-----------------------------|:-------------------------------------------|:-------------------|
+|  0 | ['Hello from John Snow Labs ! '] | ['Hello from John Snow Labs !'] | ['Hello', 'from', 'John', 'Snow', 'Labs', '!'] | [[-0.147406503558158,.,...]] | ['O', 'O', 'B-ORG', 'I-ORG', 'I-ORG', 'O'] | ['John Snow Labs'] |
+
+
+{:.model-param}
+```
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|onto_recognize_entities_bert_mini|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 4.4.2+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|57.6 MB|
+
+## Included Models
+
+- DocumentAssembler
+- SentenceDetectorDLModel
+- TokenizerModel
+- BertEmbeddings
+- NerDLModel
+- NerConverter