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  • John Snow Labs
  • Jun 21, 2023

German Electra Embeddings (from deepset)

  • de
  • open_source
  • electra
  • embeddings
  • onnx

Description

Pretrained Electra Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. gelectra-base-generator is a German model orginally trained by deepset.

Predicted Entities

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How to use

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

tokenizer = Tokenizer() \
    .setInputCols("document") \
    .setOutputCol("token")
  
embeddings = BertEmbeddings.pretrained("electra_embeddings_gelectra_base_generator","de") \
    .setInputCols(["document", "token"]) \
    .setOutputCol("embeddings")
    
pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings])

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

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

val documentAssembler = new DocumentAssembler() 
      .setInputCol("text") 
      .setOutputCol("document")
 
val tokenizer = new Tokenizer() 
    .setInputCols(Array("document"))
    .setOutputCol("token")

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

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

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

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

import nlu
nlu.load("de.embed.electra.base").predict("""Ich liebe Spark NLP""")

Model Information

Model Name: electra_embeddings_gelectra_base_generator
Compatibility: Spark NLP 5.0.0+
License: Open Source
Edition: Official
Input Labels: [sentence, token]
Output Labels: [embeddings]
Language: de
Size: 127.6 MB
Case sensitive: true