Description
Pretrained RobertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. covid-policy-roberta-21 is a English model originally trained by MoritzLaurer.
Predicted Entities
Quarantine, Health Monitoring, Lockdown, Restrictions of Mass Gatherings, Health Testing, Public Awareness Measures, Closure and Regulation of Schools, Restriction and Regulation of Businesses, COVID-19 Vaccines, Other Policy Not Listed Above, Internal Border Restrictions, Restriction and Regulation of Government Services, Curfew, Social Distancing, Health Resources, External Border Restrictions, Anti-Disinformation Measures, Hygiene, Other, Declaration of Emergency
How to use
documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")
tokenizer = Tokenizer() \
.setInputCols("document") \
.setOutputCol("token")
seq_classifier = RoBertaForSequenceClassification.pretrained("roberta_classifier_covid_policy_21","en") \
.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_covid_policy_21","en")
.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("en.classify.roberta.covid.by_moritzlaurer").predict("""PUT YOUR STRING HERE""")
Model Information
| Model Name: | roberta_classifier_covid_policy_21 |
| Compatibility: | Spark NLP 5.2.0+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [document, token] |
| Output Labels: | [class] |
| Language: | en |
| Size: | 309.1 MB |
| Case sensitive: | true |
| Max sentence length: | 256 |
References
References
- https://huggingface.co/MoritzLaurer/covid-policy-roberta-21
- https://www.ceps.eu/ceps-staff/moritz-laurer/