Dutch BertForMaskedLM Base Cased model (from GroNLP)

Description

Pretrained BertForMaskedLM model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. bert-base-dutch-cased is a Dutch model originally trained by GroNLP.

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How to use

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

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

bert_loaded = BertEmbeddings.pretrained("bert_embeddings_base_dutch_cased","nl") \
    .setInputCols(["document", "token"]) \
    .setOutputCol("embeddings") \
    .setCaseSensitive(True)

pipeline = Pipeline(stages=[documentAssembler, tokenizer, bert_loaded])

data = spark.createDataFrame([["I love Spark NLP"]]).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 bert_loaded = BertEmbeddings.pretrained("bert_embeddings_base_dutch_cased","nl")
    .setInputCols(Array("document", "token"))
    .setOutputCol("embeddings")
    .setCaseSensitive(True)

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

val data = Seq("I love Spark NLP").toDS.toDF("text")

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

import nlu
nlu.load("nl.embed.bert.cased_base").predict("""I love Spark NLP""")

Model Information

Model Name:	bert_embeddings_base_dutch_cased
Compatibility:	Spark NLP 4.2.4+
License:	Open Source
Edition:	Official
Input Labels:	[sentence, token]
Output Labels:	[bert]
Language:	nl
Size:	409.5 MB
Case sensitive:	true

References

https://huggingface.co/GroNLP/bert-base-dutch-cased
https://www.semanticscholar.org/author/Wietse-de-Vries/144611157
https://www.semanticscholar.org/author/Andreas-van-Cranenburgh/2791585
https://www.semanticscholar.org/author/Arianna-Bisazza/3242253
https://www.semanticscholar.org/author/Tommaso-Caselli/1864635
https://www.semanticscholar.org/author/Gertjan-van-Noord/143715131
https://www.semanticscholar.org/author/M.-Nissim/2742475
https://arxiv.org/abs/1912.09582
https://github.com/wietsedv/bertje
https://www.semanticscholar.org/paper/BERTje%3A-A-Dutch-BERT-Model-Vries-Cranenburgh/a4d5e425cac0bf84c86c0c9f720b6339d6288ffa
https://www.clips.uantwerpen.be/conll2002/ner/
https://ivdnt.org/downloads/taalmaterialen/tstc-sonar-corpus
https://github.com/google-research/bert/blob/master/multilingual.md
http://textdata.nl
https://github.com/iPieter/RobBERT
https://universaldependencies.org/treebanks/nl_lassysmall/index.html
https://github.com/google-research/bert/blob/master/multilingual.md
http://textdata.nl
https://github.com/iPieter/RobBERT

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