2023-11-06-bert_ner_alexander_learn_bert_finetuned_ner_accelerate_en

docs/_posts/ahmedlone127/2023-11-06-bert_ner_aditya22_bert_finetuned_ner_en.md

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+---
+layout: model
+title: English BertForTokenClassification Cased model (from aditya22)
+author: John Snow Labs
+name: bert_ner_aditya22_bert_finetuned_ner
+date: 2023-11-06
+tags: [bert, ner, open_source, en, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-finetuned-ner` is a English model originally trained by `aditya22`.
+
+## Predicted Entities
+
+`ORG`, `LOC`, `MISC`, `PER`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ner_aditya22_bert_finetuned_ner_en_5.2.0_3.0_1699284189318.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ner_aditya22_bert_finetuned_ner_en_5.2.0_3.0_1699284189318.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+        .setInputCol("text") \
+        .setOutputCol("document")
+
+sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")\
+       .setInputCols(["document"])\
+       .setOutputCol("sentence")
+
+tokenizer = Tokenizer() \
+    .setInputCols("sentence") \
+    .setOutputCol("token")
+
+tokenClassifier = BertForTokenClassification.pretrained("bert_ner_aditya22_bert_finetuned_ner","en") \
+    .setInputCols(["sentence", "token"]) \
+    .setOutputCol("ner")
+
+pipeline = Pipeline(stages=[documentAssembler, sentenceDetector, tokenizer, tokenClassifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+          .setInputCol("text") 
+          .setOutputCol("document")
+
+val sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+       .setInputCols(Array("document"))
+       .setOutputCol("sentence")
+
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("sentence"))
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_ner_aditya22_bert_finetuned_ner","en") 
+    .setInputCols(Array("sentence", "token")) 
+    .setOutputCol("ner")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler,sentenceDetector, tokenizer, tokenClassifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.ner.bert.conll.finetuned.by_aditya22").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_ner_aditya22_bert_finetuned_ner|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+|Case sensitive:|true|
+|Max sentence length:|128|
+
+## References
+
+References
+
+- https://huggingface.co/aditya22/bert-finetuned-ner
+- https://paperswithcode.com/sota?task=Token+Classification&dataset=conll2003

docs/_posts/ahmedlone127/2023-11-06-bert_ner_airi_bert_finetuned_ner_en.md

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+---
+layout: model
+title: English BertForTokenClassification Cased model (from airi)
+author: John Snow Labs
+name: bert_ner_airi_bert_finetuned_ner
+date: 2023-11-06
+tags: [bert, ner, open_source, en, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-finetuned-ner` is a English model originally trained by `airi`.
+
+## Predicted Entities
+
+`ORG`, `LOC`, `MISC`, `PER`
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ner_airi_bert_finetuned_ner_en_5.2.0_3.0_1699282984146.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ner_airi_bert_finetuned_ner_en_5.2.0_3.0_1699282984146.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = DocumentAssembler() \
+        .setInputCol("text") \
+        .setOutputCol("document")
+
+sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")\
+       .setInputCols(["document"])\
+       .setOutputCol("sentence")
+
+tokenizer = Tokenizer() \
+    .setInputCols("sentence") \
+    .setOutputCol("token")
+
+tokenClassifier = BertForTokenClassification.pretrained("bert_ner_airi_bert_finetuned_ner","en") \
+    .setInputCols(["sentence", "token"]) \
+    .setOutputCol("ner")
+
+pipeline = Pipeline(stages=[documentAssembler, sentenceDetector, tokenizer, tokenClassifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new DocumentAssembler() 
+          .setInputCol("text") 
+          .setOutputCol("document")
+
+val sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
+       .setInputCols(Array("document"))
+       .setOutputCol("sentence")
+
+val tokenizer = new Tokenizer() 
+    .setInputCols(Array("sentence"))
+    .setOutputCol("token")
+
+val tokenClassifier = BertForTokenClassification.pretrained("bert_ner_airi_bert_finetuned_ner","en") 
+    .setInputCols(Array("sentence", "token")) 
+    .setOutputCol("ner")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler,sentenceDetector, tokenizer, tokenClassifier))
+
+val data = Seq("PUT YOUR STRING HERE").toDF("text")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.ner.bert.airi..by_airi").predict("""PUT YOUR STRING HERE""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_ner_airi_bert_finetuned_ner|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|665.1 MB|
+|Case sensitive:|true|
+|Max sentence length:|128|
+
+## References
+
+References
+
+- https://huggingface.co/airi/bert-finetuned-ner

docs/_posts/ahmedlone127/2023-11-06-bert_ner_ajgp_bert_finetuned_ner_en.md

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+---
+layout: model
+title: English bert_ner_ajgp_bert_finetuned_ner BertForTokenClassification from AJGP
+author: John Snow Labs
+name: bert_ner_ajgp_bert_finetuned_ner
+date: 2023-11-06
+tags: [bert, en, open_source, token_classification, onnx]
+task: Named Entity Recognition
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForTokenClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ner_ajgp_bert_finetuned_ner` is a English model originally trained by AJGP.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ner_ajgp_bert_finetuned_ner_en_5.2.0_3.0_1699270662024.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ner_ajgp_bert_finetuned_ner_en_5.2.0_3.0_1699270662024.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+
+documentAssembler = DocumentAssembler() \
+    .setInputCol("text") \
+    .setOutputCol("documents")
+
+
+tokenClassifier = BertForTokenClassification.pretrained("bert_ner_ajgp_bert_finetuned_ner","en") \
+            .setInputCols(["documents","token"]) \
+            .setOutputCol("ner")
+
+pipeline = Pipeline().setStages([documentAssembler, tokenClassifier])
+
+pipelineModel = pipeline.fit(data)
+
+pipelineDF = pipelineModel.transform(data)
+
+```
+```scala
+
+
+val documentAssembler = new DocumentAssembler()
+    .setInputCol("text") 
+    .setOutputCol("embeddings")
+
+val tokenClassifier = BertForTokenClassification  
+    .pretrained("bert_ner_ajgp_bert_finetuned_ner", "en")
+    .setInputCols(Array("documents","token")) 
+    .setOutputCol("ner") 
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenClassifier))
+
+val pipelineModel = pipeline.fit(data)
+
+val pipelineDF = pipelineModel.transform(data)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_ner_ajgp_bert_finetuned_ner|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[documents, token]|
+|Output Labels:|[ner]|
+|Language:|en|
+|Size:|403.7 MB|
+
+## References
+
+https://huggingface.co/AJGP/bert-finetuned-ner