Description
Pretrained CamembertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. test_tcp_ca is a English model originally trained by cassandra-themis.
Predicted Entities
date_du_jugement, juridiction_decision, date_de_naissance, formation_jugement, date_de_decision, formation_decision, juridiction_jugement, condamne, id_jugement, id_decision, defendeur, demandeur
How to use
documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")
sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")\
.setInputCols(["document"])\
.setOutputCol("sentence")
tokenizer = Tokenizer() \
.setInputCols("sentence") \
.setOutputCol("token")
sequenceClassifier_loaded = CamemBertForTokenClassification.pretrained("camembert_classifier_test_tcp_ca_cassandra_themis","en") \
.setInputCols(["sentence", "token"]) \
.setOutputCol("ner")
pipeline = Pipeline(stages=[documentAssembler,sentenceDetector,tokenizer,sequenceClassifier_loaded])
data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
result = pipeline.fit(data).transform(data)
val documentAssembler = new DocumentAssembler()
.setInputCol("text")
.setOutputCol("document")
val sentenceDetector = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx")
.setInputCols(Array("document"))
.setOutputCol("sentence")
val tokenizer = new Tokenizer()
.setInputCols(Array("sentence"))
.setOutputCol("token")
val sequenceClassifier_loaded = CamemBertForTokenClassification.pretrained("camembert_classifier_test_tcp_ca_cassandra_themis","en")
.setInputCols(Array("sentence", "token"))
.setOutputCol("ner")
val pipeline = new Pipeline().setStages(Array(documentAssembler,sentenceDetector,tokenizer,sequenceClassifier_loaded))
val data = Seq("PUT YOUR STRING HERE").toDF("text")
val result = pipeline.fit(data).transform(data)
import nlu
nlu.load("en.ner.camembert.by_cassandra_themis").predict("""PUT YOUR STRING HERE""")
Model Information
| Model Name: | camembert_classifier_test_tcp_ca_cassandra_themis |
| Compatibility: | Spark NLP 4.2.0+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [document, token] |
| Output Labels: | [class] |
| Language: | en |
| Size: | 413.5 MB |
| Case sensitive: | true |
| Max sentence length: | 256 |
References
- https://huggingface.co/cassandra-themis/test_tcp_ca