Description
Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. mBERT-base-Biomedical-NER is a English model originally trained by StivenLancheros.
Predicted Entities
GENE, Chemical, Protein, Cell, Sequence, Taxon
How to use
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_mBERT_base_Biomedical_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)
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_mBERT_base_Biomedical_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)
Model Information
| Model Name: | bert_ner_mBERT_base_Biomedical_NER | 
| Compatibility: | Spark NLP 4.1.0+ | 
| License: | Open Source | 
| Edition: | Official | 
| Input Labels: | [document, token] | 
| Output Labels: | [ner] | 
| Language: | en | 
| Size: | 665.6 MB | 
| Case sensitive: | true | 
| Max sentence length: | 128 | 
References
- https://huggingface.co/StivenLancheros/mBERT-base-Biomedical-NER