German Bert Embeddings (from Geotrend)


Pretrained Bert Embeddings model, uploaded to Hugging Face, adapted and imported into Spark NLP. bert-base-de-cased is a German model orginally trained by Geotrend.

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How to use

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

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

embeddings = BertEmbeddings.pretrained("bert_embeddings_bert_base_de_cased","de") \
.setInputCols(["document", "token"]) \

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

data = spark.createDataFrame([["Ich liebe Funken NLP"]]).toDF("text")

result =
val documentAssembler = new DocumentAssembler() 

val tokenizer = new Tokenizer() 

val embeddings = BertEmbeddings.pretrained("bert_embeddings_bert_base_de_cased","de") 
.setInputCols(Array("document", "token")) 

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

val data = Seq("Ich liebe Funken NLP").toDF("text")

val result =
import nlu
nlu.load("de.embed.bert_base_de_cased").predict("""Ich liebe Funken NLP""")

Model Information

Model Name: bert_embeddings_bert_base_de_cased
Compatibility: Spark NLP 3.4.2+
License: Open Source
Edition: Official
Input Labels: [sentence, token]
Output Labels: [bert]
Language: de
Size: 398.2 MB
Case sensitive: true