Description
Pretrained XLMRoBERTa Embeddings model, uploaded to Hugging Face, adapted and imported into Spark NLP. indic-transformers-hi-xlmroberta
is a Hindi model orginally trained by neuralspace-reverie
.
How to use
documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")
tokenizer = Tokenizer() \
.setInputCols("document") \
.setOutputCol("token")
embeddings = XlmRoBertaEmbeddings.pretrained("xlmroberta_embeddings_indic_transformers_hi_xlmroberta","hi") \
.setInputCols(["document", "token"]) \
.setOutputCol("embeddings")
pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings])
data = spark.createDataFrame([["मुझे स्पार्क एनएलपी बहुत पसंद है"]]).toDF("text")
result = pipeline.fit(data).transform(data)
val documentAssembler = new DocumentAssembler()
.setInputCol("text")
.setOutputCol("document")
val tokenizer = new Tokenizer()
.setInputCols(Array("document"))
.setOutputCol("token")
val embeddings = XlmRoBertaEmbeddings.pretrained("xlmroberta_embeddings_indic_transformers_hi_xlmroberta","hi")
.setInputCols(Array("document", "token"))
.setOutputCol("embeddings")
val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))
val data = Seq("मुझे स्पार्क एनएलपी बहुत पसंद है").toDF("text")
val result = pipeline.fit(data).transform(data)
Model Information
Model Name: | xlmroberta_embeddings_indic_transformers_hi_xlmroberta |
Compatibility: | Spark NLP 3.4.4+ |
License: | Open Source |
Edition: | Official |
Input Labels: | [sentence, token] |
Output Labels: | [embeddings] |
Language: | hi |
Size: | 505.0 MB |
Case sensitive: | true |
References
- https://huggingface.co/neuralspace-reverie/indic-transformers-hi-xlmroberta
- https://oscar-corpus.com/