Description
Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.roberta_ner_roberta_persian_farsi_zwnj_base_ner is a Persian model originally trained by HooshvareLab.
How to use
documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")
tokenizer = Tokenizer() \
.setInputCols(["document"]) \
.setOutputCol("token")
tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_ner_roberta_persian_farsi_zwnj_base_ner","fa") \
.setInputCols(["document","token"]) \
.setOutputCol("ner")
pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier])
pipelineModel = pipeline.fit(data)
pipelineDF = pipelineModel.transform(data)
val documentAssembler = new DocumentAssembler()
.setInputCol("text")
.setOutputCol("document")
val tokenizer = Tokenizer() \
.setInputCols(Array("document")) \
.setOutputCol("token")
val tokenClassifier = RoBertaForTokenClassification
.pretrained("roberta_ner_roberta_persian_farsi_zwnj_base_ner", "fa")
.setInputCols(Array("document","token"))
.setOutputCol("ner")
val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier))
val pipelineModel = pipeline.fit(data)
val pipelineDF = pipelineModel.transform(data)
Model Information
| Model Name: | roberta_ner_roberta_persian_farsi_zwnj_base_ner |
| Compatibility: | Spark NLP 5.2.1+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [documents, token] |
| Output Labels: | [ner] |
| Language: | fa |
| Size: | 442.1 MB |
References
https://huggingface.co/HooshvareLab/roberta-fa-zwnj-base-ner