Description
Pretrained AlbertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.albert_persian_farsi_base_v2_ner_peyma
is a Persian model originally trained by m3hrdadfi.
How to use
document_assembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("documents")
sequenceClassifier = AlbertForTokenClassification.pretrained("albert_persian_farsi_base_v2_ner_peyma","fa") \
.setInputCols(["documents","token"]) \
.setOutputCol("ner")
pipeline = Pipeline().setStages([document_assembler, sequenceClassifier])
pipelineModel = pipeline.fit(data)
pipelineDF = pipelineModel.transform(data)
val document_assembler = new DocumentAssembler()
.setInputCol("text")
.setOutputCol("embeddings")
val sequenceClassifier = AlbertForTokenClassification
.pretrained("albert_persian_farsi_base_v2_ner_peyma", "fa")
.setInputCols(Array("documents","token"))
.setOutputCol("ner")
val pipeline = new Pipeline().setStages(Array(document_assembler, sequenceClassifier))
val pipelineModel = pipeline.fit(data)
val pipelineDF = pipelineModel.transform(data)
Model Information
Model Name: | albert_persian_farsi_base_v2_ner_peyma |
Compatibility: | Spark NLP 5.1.2+ |
License: | Open Source |
Edition: | Official |
Input Labels: | [documents, token] |
Output Labels: | [ner] |
Language: | fa |
Size: | 66.4 MB |
References
https://huggingface.co/m3hrdadfi/albert-fa-base-v2-ner-peyma