English Legal Longformer Base Embeddings Model

Description

Pretrained Legal Longformer Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. legal-longformer-base is a English model originally trained by lexlms.

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How to use

documentAssembler = DocumentAssembler() \
    .setInputCols("text") \
    .setOutputCols("document")

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

embeddings = LongformerEmbeddings.pretrained("longformer_base_english_legal","en") \
    .setInputCols(["document", "token"]) \
    .setOutputCol("embeddings") \
    .setCaseSensitive(True)
    
pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings])

data = spark.createDataFrame([["I love Spark NLP"]]).toDF("text")

result = pipeline.fit(data).transform(data)
val documentAssembler = new DocumentAssembler() 
    .setInputCols(Array("text")) 
    .setOutputCols(Array("document"))
      
val tokenizer = new Tokenizer()
    .setInputCols("document")
    .setOutputCol("token")
 
val embeddings = LongformerEmbeddings.pretrained("longformer_base_english_legal","en") 
    .setInputCols(Array("document", "token"))
    .setOutputCol("embeddings")
    .setCaseSensitive(True)    
   
val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))

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

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

Model Information

Model Name: longformer_base_english_legal
Compatibility: Spark NLP 4.4.2+
License: Open Source
Edition: Official
Input Labels: [sentence, token]
Output Labels: [embeddings]
Language: en
Size: 561.6 MB
Case sensitive: true
Max sentence length: 4096

References

https://huggingface.co/lexlms/legal-longformer-base