Description
Named Entity Recognition trained on English panx
Predicted Entities
How to use
documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")
tokenizer = Tokenizer() \
.setInputCols(["document"]) \
.setOutputCol("token")
token_classifier = XlmRoBertaForTokenClassification.pretrained("deepa_xlmroberta_ner_large_en_panx", "en") \
.setInputCols(["document", "token"]) \
.setOutputCol("ner")
ner_converter = NerConverter() \
.setInputCols(["document", "token", "ner"]) \
.setOutputCol("ner_chunk")
pipeline = Pipeline(stages=[documentAssembler, tokenizer, token_classifier, ner_converter])
Model Information
| Model Name: | deepa_xlmroberta_ner_large_en_panx |
| Compatibility: | Spark NLP 4.1.0+ |
| License: | Open Source |
| Edition: | Community |
| Input Labels: | [document, token] |
| Output Labels: | [ner] |
| Language: | en |
| Size: | 1.8 GB |
| Case sensitive: | true |
| Max sentence length: | 256 |