Vietnamese Deberta Embeddings model (from hieule)

Description

Pretrained DebertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. spm-vie-deberta is a Vietnamese model originally trained by hieule.

Predicted Entities

Download Copy S3 URI

How to use

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

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

embeddings = DeBertaEmbeddings.pretrained("deberta_embeddings_spm_vie","vie") \
    .setInputCols(["document", "token"]) \
    .setOutputCol("embeddings") \
    .setCaseSensitive(True)

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

data = spark.createDataFrame([["I love Spark NLP"]]).toDF("text")

result = pipeline.fit(data).transform(data)

val documentAssembler = new DocumentAssembler()
    .setInputCol("text")
    .setOutputCol("document")

val tokenizer = new Tokenizer()
    .setInputCols("document")
    .setOutputCol("token")

val embeddings = DeBertaEmbeddings.pretrained("deberta_embeddings_spm_vie","vie")
    .setInputCols(Array("document", "token"))
    .setOutputCol("embeddings")
    .setCaseSensitive(true)

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

val data = Seq("I love Spark NLP").toDS.toDF("text")

val result = pipeline.fit(data).transform(data)

Model Information

Model Name:	deberta_embeddings_spm_vie
Compatibility:	Spark NLP 5.0.0+
License:	Open Source
Edition:	Official
Input Labels:	[sentence, token]
Output Labels:	[embeddings]
Language:	vie
Size:	289.7 MB
Case sensitive:	false

PREVIOUSEnglish Deberta Embeddings model (from domenicrosati)

NEXTEnglish Deberta Embeddings model (from ZZ99)