Description
Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. EpiExtract4GARD-v2
is a English model originally trained by ncats
.
Predicted Entities
ETHN
, LOC
, SEX
, DATE
, STAT
, EPI
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_EpiExtract4GARD_v2","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_EpiExtract4GARD_v2","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_EpiExtract4GARD_v2 |
Compatibility: | Spark NLP 4.0.0+ |
License: | Open Source |
Edition: | Official |
Input Labels: | [document, token] |
Output Labels: | [ner] |
Language: | en |
Size: | 1.3 GB |
Case sensitive: | true |
Max sentence length: | 128 |
References
- https://huggingface.co/ncats/EpiExtract4GARD-v2
- https://github.com/ncats/epi4GARD/blob/master/EpiExtract4GARD/extract_abs.py
- https://github.com/ncats/epi4GARD/blob/master/EpiExtract4GARD/gard-id-name-synonyms.json
- https://github.com/ncats/epi4GARD/tree/master/EpiExtract4GARD#epiextract4gard
- https://aws.amazon.com/ec2/instance-types/
- https://pubmed.ncbi.nlm.nih.gov/21659675/
- https://github.com/ncats/epi4GARD/blob/master/EpiExtract4GARD/Case%20Study.ipynb
- https://github.com/wzkariampuzha
- https://github.com/ncats/epi4GARD/blob/master/EpiExtract4GARD/classify_abs.py