Description
Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. roberta-base-ca-finetuned-tecla
is a Catalan model originally trained by JonatanGk
.
Predicted Entities
Salut
, Món
, Unió_Europea
, Govern
, Educació
, Mobilitat
, Successos
, Meteorologia
, Lletres
, Trànsit
, Cinema
, Cultura
, Govern_espanyol
, Música
, Comerç
, Empresa
, Economia
, Infraestructures
, Societat
, Festa_i_cultura_popular
, Política
, Policial
, Medi_ambient
, Judicial
, Turisme
, Teatre
, Parlament
, Partits
, Treball
, Equipaments_i_patrimoni
How to use
documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")
tokenizer = Tokenizer() \
.setInputCols("document") \
.setOutputCol("token")
seq_classifier = RoBertaForSequenceClassification.pretrained("roberta_classifier_base_ca_finetuned_tecla","ca") \
.setInputCols(["document", "token"]) \
.setOutputCol("class")
pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier])
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 seq_classifier = RoBertaForSequenceClassification.pretrained("roberta_classifier_base_ca_finetuned_tecla","ca")
.setInputCols(Array("document", "token"))
.setOutputCol("class")
val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier))
val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")
val result = pipeline.fit(data).transform(data)
import nlu
nlu.load("ca.classify.roberta.base_finetuned.by_jonatangk").predict("""PUT YOUR STRING HERE""")
Model Information
Model Name: | roberta_classifier_base_ca_finetuned_tecla |
Compatibility: | Spark NLP 4.1.0+ |
License: | Open Source |
Edition: | Official |
Input Labels: | [document, token] |
Output Labels: | [class] |
Language: | ca |
Size: | 471.4 MB |
Case sensitive: | true |
Max sentence length: | 256 |
References
- https://huggingface.co/JonatanGk/roberta-base-ca-finetuned-tecla
- https://paperswithcode.com/sota?task=Text+Classification&dataset=tecla