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 eduardopds
.
Predicted Entities
ORG
, LOC
, PER
, MISC
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_eduardopds_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)
Model Information
Model Name: | bert_ner_eduardopds_bert_finetuned_ner |
Compatibility: | Spark NLP 4.1.0+ |
License: | Open Source |
Edition: | Official |
Input Labels: | [document, token] |
Output Labels: | [ner] |
Language: | en |
Size: | 404.2 MB |
Case sensitive: | true |
Max sentence length: | 128 |
References
- https://huggingface.co/eduardopds/bert-finetuned-ner