Description
Pretrained Spanish Legal Word Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. legalectra-small-spanish is a English model originally trained by mrm8488.
Predicted Entities
How to use
documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")
tokenizer = Tokenizer() \
.setInputCols("document") \
.setOutputCol("token")
electra = BertEmbeddings.pretrained("legalectra_small","es") \
.setInputCols(["document", "token"]) \
.setOutputCol("embeddings")
pipeline = Pipeline(stages=[documentAssembler, tokenizer, electra])
data = spark.createDataFrame([["Amo a Spark NLP."]]).toDF("text")
result = pipeline.fit(data).transform(data)
val documentAssembler = new DocumentAssembler()
.setInputCol("text")
.setOutputCol("document")
val tokenizer = new Tokenizer()
.setInputCols(Array("document"))
.setOutputCol("token")
val electra = BertEmbeddings.pretrained("legalectra_small","es")
.setInputCols(Array("document", "token"))
.setOutputCol("class")
val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, electra))
val data = Seq("Amo a Spark NLP.").toDS.toDF("text")
val result = pipeline.fit(data).transform(data)
import nlu
nlu.load("es.embed.bert.small_legal").predict("""Amo a Spark NLP.""")
Model Information
| Model Name: | legalectra_small |
| Compatibility: | Spark NLP 5.0.0+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [sentence, token] |
| Output Labels: | [bert] |
| Language: | es |
| Size: | 51.2 MB |
| Case sensitive: | true |