Multilingual XLMRoBerta Embeddings (from hfl)

Description

Pretrained XLMRoBERTa Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. cino-large is a Multilingual model orginally trained by hfl.

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_cino_large", "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_large", "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.large.by_hfl").predict("""PUT YOUR STRING HERE""")

Model Information

Model Name: xlmroberta_embeddings_cino_large
Compatibility: Spark NLP 3.4.4+
License: Open Source
Edition: Official
Input Labels: [sentence, token]
Output Labels: [embeddings]
Language: xx
Size: 2.2 GB
Case sensitive: true

References

  • https://huggingface.co/hfl/cino-large
  • 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