Persian RoBERTa Embeddings (from HooshvareLab)

Description

Pretrained RoBERTa Embeddings model, uploaded to Hugging Face, adapted and imported into Spark NLP. roberta-fa-zwnj-base is a Persian model orginally trained by HooshvareLab.

Download Copy S3 URI

How to use

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

tokenizer = Tokenizer() \
.setInputCols("document") \
.setOutputCol("token")

embeddings = RoBertaEmbeddings.pretrained("roberta_embeddings_roberta_fa_zwnj_base","fa") \
.setInputCols(["document", "token"]) \
.setOutputCol("embeddings")

pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings])

data = spark.createDataFrame([["من عاشق جرقه NLP هستم"]]).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 = RoBertaEmbeddings.pretrained("roberta_embeddings_roberta_fa_zwnj_base","fa") 
.setInputCols(Array("document", "token")) 
.setOutputCol("embeddings")

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

val data = Seq("من عاشق جرقه NLP هستم").toDF("text")

val result = pipeline.fit(data).transform(data)
import nlu
nlu.load("fa.embed.roberta_fa_zwnj_base").predict("""من عاشق جرقه NLP هستم""")

Model Information

Model Name: roberta_embeddings_roberta_fa_zwnj_base
Compatibility: Spark NLP 3.4.2+
License: Open Source
Edition: Official
Input Labels: [sentence, token]
Output Labels: [bert]
Language: fa
Size: 444.9 MB
Case sensitive: true

References

  • https://huggingface.co/HooshvareLab/roberta-fa-zwnj-base
  • https://github.com/hooshvare/roberta/issues