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.
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