English Legal BERT Embedding Base Uncased model

Description

Pretrained BERT Embedding model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. legal-bert-base-uncased-finetuned-RRamicus is a English model originally trained by repro-rights-amicus-briefs.

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How to use

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

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

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

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

Model Information

Model Name: bert_embeddings_legal_bert_base_uncased_finetuned_RRamicus
Compatibility: Spark NLP 4.2.7+
License: Open Source
Edition: Official
Input Labels: [sentence]
Output Labels: [bert_sentence]
Language: en
Size: 409.8 MB
Case sensitive: false
Max sentence length: 128

References

  • https://huggingface.co/repro-rights-amicus-briefs/legal-bert-base-uncased-finetuned-RRamicus