Description
Pretrained RoBERTa Embeddings model, uploaded to Hugging Face, adapted and imported into Spark NLP. robbertje-1-gb-bort is a Dutch model orginally trained by DTAI-KULeuven.
How to use
documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")
tokenizer = Tokenizer() \
.setInputCols("document") \
.setOutputCol("token")
embeddings = RoBertaEmbeddings.pretrained("roberta_embeddings_robbertje_1_gb_bort","nl") \
.setInputCols(["document", "token"]) \
.setOutputCol("embeddings")
pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings])
data = spark.createDataFrame([["Ik hou van vonk 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 = RoBertaEmbeddings.pretrained("roberta_embeddings_robbertje_1_gb_bort","nl")
.setInputCols(Array("document", "token"))
.setOutputCol("embeddings")
val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
val data = Seq("Ik hou van vonk nlp").toDF("text")
val result = pipeline.fit(data).transform(data)
import nlu
nlu.load("nl.embed.robbertje_1_gb_bort").predict("""Ik hou van vonk nlp""")
Model Information
| Model Name: | roberta_embeddings_robbertje_1_gb_bort |
| Compatibility: | Spark NLP 3.4.2+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [sentence, token] |
| Output Labels: | [bert] |
| Language: | nl |
| Size: | 172.8 MB |
| Case sensitive: | true |
References
- https://huggingface.co/DTAI-KULeuven/robbertje-1-gb-bort
- http://github.com/iPieter/robbert
- http://github.com/iPieter/robbertje
- https://www.clinjournal.org/clinj/article/view/131
- https://www.clin31.ugent.be
- https://arxiv.org/abs/2101.05716