Description
Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. autotrain-country-recognition-1059336697 is a English model originally trained by mhaegeman.
Predicted Entities
Turkey, United States, Austria, Finland, South Africa, Norway, Portugal, Netherlands, Poland, France, United Arab Emirates, United Kingdom, Belgium, Italy, Germany, Saudi Arabia, Denmark, Spain, Sweden, Israel, Switzerland
How to use
documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")
tokenizer = Tokenizer() \
.setInputCols("document") \
.setOutputCol("token")
sequenceClassifier_loaded = DistilBertForSequenceClassification.pretrained("distilbert_sequence_classifier_autotrain_country_recognition_1059336697","en") \
.setInputCols(["document", "token"]) \
.setOutputCol("class")
pipeline = Pipeline(stages=[documentAssembler, 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 tokenizer = new Tokenizer()
.setInputCols(Array("document"))
.setOutputCol("token")
val sequenceClassifier_loaded = DistilBertForSequenceClassification.pretrained("distilbert_sequence_classifier_autotrain_country_recognition_1059336697","en")
.setInputCols(Array("document", "token"))
.setOutputCol("class")
val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer,sequenceClassifier_loaded))
val data = Seq("PUT YOUR STRING HERE").toDF("text")
val result = pipeline.fit(data).transform(data)
import nlu
nlu.load("en.classify.distil_bert.by_mhaegeman").predict("""PUT YOUR STRING HERE""")
Model Information
| Model Name: | distilbert_sequence_classifier_autotrain_country_recognition_1059336697 |
| Compatibility: | Spark NLP 4.1.0+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [document, token] |
| Output Labels: | [ner] |
| Language: | en |
| Size: | 249.8 MB |
| Case sensitive: | true |
| Max sentence length: | 128 |
References
- https://huggingface.co/mhaegeman/autotrain-country-recognition-1059336697