English DistilBERT Embeddings Cased model (from mrm8488)

Description

Pretrained DistilBERT Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. distilbert_embeddings_finetuned_sarcasm_classification is a English model originally trained by mrm8488.

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How to use

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

tokenizer = Tokenizer() \
    .setInputCols("document") \
    .setOutputCol("token")
  
embeddings = DistilBertEmbeddings.pretrained("distilbert_embeddings_finetuned_sarcasm_classification","en") \
    .setInputCols(["document", "token"]) \
    .setOutputCol("embeddings")
    
pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings])

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(Array("document"))
    .setOutputCol("token")

val embeddings = DistilBertEmbeddings.pretrained("distilbert_embeddings_finetuned_sarcasm_classification","en") 
    .setInputCols(Array("document", "token")) 
    .setOutputCol("class")

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

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

val result = pipeline.fit(data).transform(data)
import nlu
nlu.load("en.embed.distil_bert.finetuned").predict("""PUT YOUR STRING HERE.""")

Model Information

Model Name: distilbert_embeddings_finetuned_sarcasm_classification
Compatibility: Spark NLP 4.0.0+
License: Open Source
Edition: Official
Input Labels: [sentence, token]
Output Labels: [embeddings]
Language: en
Size: 247.6 MB
Case sensitive: false

References

https://huggingface.co/mrm8488/distilbert-finetuned-sarcasm-classification