Stopwords Remover for Persian (Farsi) language (430 entries)

Description

This is a scalable, production-ready Stopwords Remover model trained using the corpus available at stopwords-iso.

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How to use

documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")

tokenizer = Tokenizer() \
.setInputCols(["document"]) \
.setOutputCol("token")

stop_words = StopWordsCleaner.pretrained("stopwords_iso","fa") \
.setInputCols(["token"]) \
.setOutputCol("cleanTokens")

pipeline = Pipeline(stages=[documentAssembler, tokenizer, stop_words]) 

example = spark.createDataFrame([["شما بهتر از من نیستید"]], ["text"]) 

results = pipeline.fit(example).transform(example)
val documentAssembler = new DocumentAssembler() 
.setInputCol("text") 
.setOutputCol("document")

val stop_words = new Tokenizer() 
.setInputCols(Array("document"))
.setOutputCol("token")

val lemmatizer = StopWordsCleaner.pretrained("stopwords_iso","fa") 
.setInputCols(Array("token")) 
.setOutputCol("cleanTokens")

val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, stop_words))
val data = Seq("شما بهتر از من نیستید").toDF("text")
val results = pipeline.fit(data).transform(data)
import nlu
nlu.load("fa.stopwords").predict("""شما بهتر از من نیستید""")

Results

+--------+
|result  |
+--------+
|[نیستید]|
+--------+

Model Information

Model Name: stopwords_iso
Compatibility: Spark NLP 3.4.1+
License: Open Source
Edition: Official
Input Labels: [token]
Output Labels: [cleanTokens]
Language: fa
Size: 3.0 KB