Multilingual XLMRoBerta Embeddings (from coastalcph)

Description

Pretrained XLMRoBERTa Embeddings model, uploaded to Hugging Face, adapted and imported into Spark NLP. fairlex-fscs-minilm is a Multilingual model orginally trained by coastalcph.

Predicted Entities

Download Copy S3 URI

How to use

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

tokenizer = Tokenizer() \
    .setInputCols("document") \
    .setOutputCol("token")
  
embeddings = XlmRoBertaEmbeddings.pretrained("xlmroberta_embeddings_fairlex_fscs_minilm","xx") \
    .setInputCols(["document", "token"]) \
    .setOutputCol("embeddings")
    
pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings])

data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).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 embeddings = XlmRoBertaEmbeddings.pretrained("xlmroberta_embeddings_fairlex_fscs_minilm","xx") 
    .setInputCols(Array("document", "token")) 
    .setOutputCol("embeddings")

val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))

val data = Seq("PUT YOUR STRING HERE").toDF("text")

val result = pipeline.fit(data).transform(data)
import nlu
nlu.load("xx.embed.xlmr_roberta.mini_lm_mini").predict("""PUT YOUR STRING HERE""")

Model Information

Model Name: xlmroberta_embeddings_fairlex_fscs_minilm
Compatibility: Spark NLP 5.0.2+
License: Open Source
Edition: Official
Input Labels: [sentence, token]
Output Labels: [embeddings]
Language: xx
Size: 402.9 MB
Case sensitive: true