Stopwords Remover for Hindi language (233 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","hi") \
    .setInputCols(["token"]) \
    .setOutputCol("cleanTokens")

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

example = spark.createDataFrame([["तुम मुझसे बेहतर नहीं हो"]], ["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","hi") 
    .setInputCols(Array("token")) 
    .setOutputCol("cleanTokens")

val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, stop_words))
val data = Seq("तुम मुझसे बेहतर नहीं हो").toDF("text")
val results = pipeline.fit(data).transform(data)

Results

+-------------------+
|result             |
+-------------------+
|[तुम, मुझसे, बेहतर]|
+-------------------+

Model Information

Model Name: stopwords_iso
Compatibility: Spark NLP 3.4.1+
License: Open Source
Edition: Official
Input Labels: [token]
Output Labels: [cleanTokens]
Language: hi
Size: 2.2 KB