Description
Pretrained RoBERTa Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. RoBERTinha is a Galician model originally trained by mrm8488.
Predicted Entities
How to use
documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")
tokenizer = Tokenizer() \
.setInputCols("document") \
.setOutputCol("token")
embeddings = RoBertaEmbeddings.pretrained("roberta_embeddings_robertinh","gl") \
.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()
.setInputCols(Array("text"))
.setOutputCols(Array("document"))
val tokenizer = new Tokenizer()
.setInputCols("document")
.setOutputCol("token")
val embeddings = RoBertaEmbeddings.pretrained("roberta_embeddings_robertinh","gl")
.setInputCols(Array("document", "token"))
.setOutputCol("embeddings")
val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
val result = pipeline.fit(data).transform(data)
import nlu
nlu.load("gl.embed.roberta").predict("""PUT YOUR STRING HERE""")
Model Information
| Model Name: | roberta_embeddings_robertinh |
| Compatibility: | Spark NLP 5.0.0+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [sentence, token] |
| Output Labels: | [embeddings] |
| Language: | gl |
| Size: | 311.7 MB |
| Case sensitive: | true |