Description
Pretrained CamemBERT Embedding model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. legal-distilcamembert is a French model originally trained by maastrichtlawtech.
How to use
documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")
tokenizer = Tokenizer() \
.setInputCols("document") \
.setOutputCol("token")
embeddings = CamemBertEmbeddings.pretrained("camembert_embeddings_legal_distilcamembert","fr") \
.setInputCols(["document", "token"]) \
.setOutputCol("embeddings")
pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings])
data = spark.createDataFrame([["J'adore Spark NLP"]]).toDF("text")
result = pipeline.fit(data).transform(data)
Model Information
| Model Name: | camembert_embeddings_legal_distilcamembert |
| Compatibility: | Spark NLP 4.2.7+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [sentence] |
| Output Labels: | [bert_sentence] |
| Language: | fr |
| Size: | 256.0 MB |
| Case sensitive: | true |
| Max sentence length: | 128 |
References
- https://huggingface.co/maastrichtlawtech/legal-distilcamembert
- https://antoinelouis.co
- https://www.maastrichtuniversity.nl/about-um/faculties/law/research/law-and-tech-lab