Description
Pretrained DistilBERT Embeddings model, uploaded to Hugging Face, adapted and imported into Spark NLP. distilbert-base-indonesian
is a Indonesian model orginally trained by cahya
.
How to use
documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")
tokenizer = Tokenizer() \
.setInputCols("document") \
.setOutputCol("token")
embeddings = DistilBertEmbeddings.pretrained("distilbert_embeddings_distilbert_base_indonesian","id") \
.setInputCols(["document", "token"]) \
.setOutputCol("embeddings")
pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings])
data = spark.createDataFrame([["Saya suka percikan NLP"]]).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 = DistilBertEmbeddings.pretrained("distilbert_embeddings_distilbert_base_indonesian","id")
.setInputCols(Array("document", "token"))
.setOutputCol("embeddings")
val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
val data = Seq("Saya suka percikan NLP").toDF("text")
val result = pipeline.fit(data).transform(data)
import nlu
nlu.load("id.embed.distilbert").predict("""Saya suka percikan NLP""")
Model Information
Model Name: | distilbert_embeddings_distilbert_base_indonesian |
Compatibility: | Spark NLP 3.4.2+ |
License: | Open Source |
Edition: | Official |
Input Labels: | [sentence, token] |
Output Labels: | [bert] |
Language: | id |
Size: | 253.4 MB |
Case sensitive: | true |
References
- https://huggingface.co/cahya/distilbert-base-indonesian
- https://github.com/cahya-wirawan/indonesian-language-models/tree/master/Transformers