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  • John Snow Labs
  • Jan 12, 2023

English Legal BERT Embedding Tiny Cased model

  • en
  • open_source
  • embeddings
  • bert

Description

Pretrained BERT Embedding model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. bert-tiny-finetuned-legal-definitions is a English model originally trained by muhtasham.

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How to use

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

tokenizer = Tokenizer() \
    .setInputCols("document") \
    .setOutputCol("token")
  
embeddings = BertEmbeddings.pretrained("bert_embeddings_bert_tiny_finetuned_legal_definitions","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)

import nlu
nlu.load("en.embed.bert.tiny_finetuned_legal").predict("""I love Spark NLP""")

Model Information

Model Name: bert_embeddings_bert_tiny_finetuned_legal_definitions
Compatibility: Spark NLP 4.2.7+
License: Open Source
Edition: Official
Input Labels: [sentence]
Output Labels: [bert_sentence]
Language: en
Size: 16.8 MB
Case sensitive: true
Max sentence length: 128

References

  • https://huggingface.co/muhtasham/bert-tiny-finetuned-legal-definitions