Multilingual XLMRoBerta Embeddings (from hfl)

Description

Pretrained XLMRoBERTa Embeddings model, uploaded to Hugging Face, adapted and imported into Spark NLP. cino-base-v2 is a Multilingual model orginally trained by hfl.

Live Demo Open in Colab Download Copy S3 URI

How to use

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

tokenizer = Tokenizer() \
    .setInputCols("document") \
    .setOutputCol("token")
  
embeddings = XlmRoBertaEmbeddings.pretrained("xlmroberta_embeddings_cino_base_v2","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_cino_base_v2","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.v2_base").predict("""PUT YOUR STRING HERE""")

Model Information

References

• https://huggingface.co/hfl/cino-base-v2
• https://github.com/ymcui/Chinese-Minority-PLM
• https://github.com/ymcui/MacBERT
• https://github.com/ymcui/Chinese-BERT-wwm
• https://github.com/ymcui/Chinese-ELECTRA
• https://github.com/ymcui/Chinese-XLNet
• https://github.com/airaria/TextBrewer
• https://github.com/ymcui/HFL-Anthology