German BertForTokenClassification Base Cased model (from mrm8488)

Description

Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. bert-base-german-finetuned-ler is a German model originally trained by mrm8488.

Predicted Entities

EUN, LIT, RR, INN, RS, PER, VO, UN, MRK, AN, LD, STR, GRT, ORG, GS, VT, LDS, ST, VS

Download Copy S3 URI

How to use

documentAssembler = DocumentAssembler() \
    .setInputCol("text") \
    .setOutputCol("document")

tokenizer = Tokenizer() \
    .setInputCols("document") \
    .setOutputCol("token")

tokenClassifier = BertForTokenClassification.pretrained("bert_token_classifier_base_german_finetuned_ler","de") \
    .setInputCols(["document", "token"]) \
    .setOutputCol("ner")

pipeline = Pipeline(stages=[documentAssembler, 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 tokenizer = new Tokenizer()
    .setInputCols("document")
    .setOutputCol("token")

val tokenClassifier = BertForTokenClassification.pretrained("bert_token_classifier_base_german_finetuned_ler","de")
    .setInputCols(Array("document", "token"))
    .setOutputCol("ner")

val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))

val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")

val result = pipeline.fit(data).transform(data)

import nlu
nlu.load("de.ner.bert.base_finetuned").predict("""PUT YOUR STRING HERE""")

Model Information

Model Name:	bert_token_classifier_base_german_finetuned_ler
Compatibility:	Spark NLP 4.2.4+
License:	Open Source
Edition:	Official
Input Labels:	[document, token]
Output Labels:	[class]
Language:	de
Size:	407.5 MB
Case sensitive:	true
Max sentence length:	256

References

https://huggingface.co/mrm8488/bert-base-german-finetuned-ler
https://github.com/elenanereiss/Legal-Entity-Recognition
https://github.com/elenanereiss/Legal-Entity-Recognition
http://www.rechtsprechung-im-internet.de
https://colab.research.google.com/drive/156Qrd7NsUHwA3nmQ6gXdZY0NzOvqk9AT?usp=sharing
https://github.com/elenanereiss/Legal-Entity-Recognition/blob/master/docs/Annotationsrichtlinien.pdf
https://twitter.com/mrm8488

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